The significant scale of the Internet of Things (IoT), in conjunction with its heterogeneous nature since it involves many device types, could lead the IoT to be exposed many security threats and attacks from adversaries. Game theory is a promising tool that can be used to design anti-adversary protection strategies for different network security scenarios. Traditionally, such anti-adversary strategies aim to minimize the expected number of infected/corrupted nodes. A con of such a traditional approach is that, due to limited resources available for defense, the IoT controller might have to sacrifice the protection of some nodes in order to better protect others, thus minimizing the expected number of infected nodes. This could lead to drastic consequences for the protected network as a whole since, by merely changing its behavior, the adversary might succeed with a higher probability of corrupting a few of the nodes, and thereby corrupt the network’s operation as a whole although the total number of infected nodes is reduced. In this paper, motivated by this observation, we suggest using the protection level as a payoff for the IoT controller. Under the protection level metric, we specify a minimal probability of being non-infected for each of the IoT nodes. Finally, we suggest an approach how to combine a strategy that maximizes the protection level strategy with a strategy that minimizes the expected number of infected/corrupted nodes so as to increase the joint efficiency. We provide examples to numerically illustrate the derived strategies.

Due to the open nature of wireless channels, wireless networks are susceptible to various physical layer security threats, including interference from jamming attacks. Such jamming attacks may adversely affect communication and diminish the reliability of receiving essential data and commands. Such communication reliability is crucial when an operator controls mobile objects, as a reduction in the reliability of getting commands or information might lead to drastic consequences. Specifically, we consider a communication center equipped with multiple antennas to communicate with a group of receivers (say, drones) performing missions in separate zones. In each zone for its protection, a jammer is installed to disrupt the communication of the communication center with the corresponding receiver. As a metric of communication reliability, we consider the signal-to-interference-plus-noise ratio (SINR) at the receiver. Since designing an anti-jamming strategy in such a hostile environment involves different agents, such as the communication center and the jammers, each with its own objectives, the problem is modeled within a game-theoretic framework. Traditionally, in such a background, the anti-jamming strategy aims to maximize the total SINR or throughput among all the receivers. A con of such a traditional approach is that, due to limited resources, the communication center might have to sacrifice communication with some receivers to maximize the total communication. This could compromise the joint mission as the receivers (drones) might face a lack of data. Motivated by this observation, we suggest using the minimal SINR among all the receivers as a communication metric for the group of receivers. This metric reflects the guaranteed reliability of communication with each receiver. In particular, we derive and illustrate an anti-jamming strategy in the most critical scenario for the communication node, where the communication node is unaware of the exact locations of the jammers but only their distributions, whereas the jammers know their location exactly.

The shared and open-access nature of wireless technologies makes wireless networks susceptible to interference, such as jamming, that could lead to delays in communication and result in delays with corresponding timely information updates. Such delays in information updates can be crucial when an operator controls mobile objects since their untimely updates might lead to drastic consequences. Specifically, we consider an operator communicating with drones performing a joint mission in a protected zone. The protector (jammer) employs a spherical jamming signal to jam the communication of the operator with the drones to fail their joint mission. To design an anti-jamming strategy in such a scenario involving agents (the operator and the jammer), with different objectives, game theory is employed. Traditionally, in such a background, the anti-jamming strategy aims to minimize the total information freshness reflected by the total delay in information update. A con of such a traditional approach is that, due to limited resources, the operator might have to sacrifice the delay in information update for some drones to minimize the total delay. This could fail the joint drone mission since some drones might follow outdated commands. In this paper, motivated by this observation, we suggest using the guaranteed information freshness metric as a cost function for the operator. Under this metric, we specify the maximal time passed since the last data update for each of the drones. An anti-jamming strategy is derived, and its advantage in comparison with the minimizing total information freshness strategy is illustrated.

Detecting malicious users or unauthorized activities poses a critical challenge in the realm of dynamic spectrum access. Traditionally, in such a problem, an intrusion detection system (IDS) aims to maximize the detection probability. Meanwhile in the networks or radio spectrum problems with multiple nodes or bands, respectively, protocol maximizing detection probability might lead to focusing on scanning the most plausible nodes or bands for intrusion and neglecting to scan less plausible nodes or bands for intrusion due to restricted scanning resources. To deal with this challenge in this paper we suggest a protocol maximizing fairness of detection probabilities among all the bands in the bandwidth. We consider α-fairness as fairness criteria. Moreover, the proposed detection protocol deals with the adversary, who endorses artificial intelligence (AI) enabling the adversary to not only infiltrate the bandwidth without being detected but also to do so in a less predictable manner for the IDS. The problem is modeled and solved in the framework of a two-player game. An advantage of fairness detection probability protocol in comparison with maximizing detection probability protocol is illustrated.

The paper considers a network's communication, where nodes, communicating with a base station, could differ by the access to information they have on their fading channel gain (channel state). Specifically, some of the nodes know their channel states exactly, while other nodes have only statistical state information. Such difference can be motivated by the fact that the channel gain is a function of the distance to the receiver, and some of the nodes might not know their own location, meanwhile, the others might have complete information about their own location via global positioning system (GPS). This scenario is common in IoT networks, particularly those situated in remote or challenging environments where GPS signals may be unreliable or inaccessible. The problem is modeled by a Bayesian game with latency as a communication metric. A novel approach is developed to solve such a heterogeneous problem by access to information in closed form for any number of channel states even for the continuum of them. The uniqueness of equilibrium is proven which reflects the usability of using latency metric and stability in communication based on the suggested communication protocol even when the nodes might differ by access to information about channel states. The equilibrium strategies are numerically illustrated.

In this paper, we model a joint (dual) system maintaining both radar task and communication task under the worst environmental conditions caused by hostile interference of the jammer. This model involves two maxmin problems formulated and solved in zero-sum game framework between system and jammer as players. The first problem is to find the equilibrium power allocation strategy of the system in the spectrum band to maximize communication signal-to-interference-plus-noise ratio (SINR) and radar’s SINR depending on the task the system focuses on. The second problem is to find a trade-off between the expected system’s SINR and fairness in using radar mode and communication mode by the system with $\alpha$-fairness as such criteria. Also, here we consider the jammer as an adversary supporting artificial intelligence (AI) which allows the adversary not just to obstruct the system’s functionality but also might achieve it in a less predictable way for the system. The derived solution is numerically illustrated. Moreover, we suggest an approach allowing us to find an optimal fairness coefficient, in other words, to find the most fair fairness criteria, to support both communication task and radar task.

A method for determining a dosage strategy is proposed to combat drug resistance in tumor progression. The method is based on a dynamic model for the clonal evolution of cancerous cells and considers the Pharmacokinetic/Pharmacodynamic (PKPD) modeling of combination therapy. The proposed mathematical representation models the dynamic and kinetic effects of multiple drugs on the number of cells while considering potential mutations and assuming that no cross-resistance arises. An optimization problem is then proposed to minimize the total number of cancerous cells in a finite treatment period given a limited number of treatments. The dosage schedule, including the amount of each drug to be administered and the timing, is found by solving the optimization problem. This treatment schedule is constrained to achieve a target minimum effectiveness, while also ensuring that the concentration of the drugs, individually and totally, does not exceed a prescribed toxicity threshold. The proposed optimization problem is represented as a Complementary Geometric Programming (CGP) problem. The results show that the solution of the optimization problem for combination therapy is the dosing schedule that leads to tumor eradication at the end of the treatment period. The results also investigate the tumor dynamics for all mutation types when undergoing treatment, showing that single drug therapies can fail to combat the emergence of resistance, while optimized combination therapies can reduce the amount of all mutation types during the course of treatment, thereby combating resistance.

The paper considers a multi-access channel scenario, where several users communicate with a base station, and investigates power allocation is a game-theoretic framework. The communication metric is the inverse signal-to-interference-plus-noise ratio (SINR) at the base station, which, for low SINR reflects communication delay. Each user faces a trade-off between the latency of the signal received by the base station, and the price that the user pays for using a specific amount of power that causes interference in the system. The equilibrium is derived in closed form and its uniqueness is proven. It is shown that the resulting strategy allows each user to maintain uninterrupted communication. For comparison purposes, we construct a specific three user network scenario, and study the SINR and throughput metrics. In that setting, we show that, unlike the latency metric, SINR and throughput may give rise to multiple equilibria, which may cause destabilization of communication.

We consider the communication between a source (user) and a destination in the presence of a jammer, and study resource assignment in a non-cooperative game theory framework using communication latency as the user's utility. The user switches between two different modes, i.e., the (a) regular transmission mode, according to which both players follow a Nash equilibrium; and the (b) smart transmission mode, according to which the user always implements the best response strategy. First, we consider the case in which the switching between transmission modes occurs with a given frequency. For this case we find the optimal transmission power of the user by formulating and solving a Bayesian game problem. We show that an increase in the frequency of smart transmissions leads to a decrease in communication latency and to an increase in the total transmission cost. We determine the switching frequency that optimizes the latency-cost trade off using α-fairness criteria. We also discuss the implications of the proposed latency metric on the player strategies as compared to the previously well studied signal-to-interference-plus-noise ratio (SINR) metric.

We consider the communication between a source (user) and a destination in the presence of a jammer, and study resource assignment in a non-cooperative game theory framework. A player (the user or the jammer) has incomplete information about its rival's identity in the form of uncertainty; the player only knows the probabilities that its rival is a player implementing a behavioral strategy as a follower in a Stackelberg game (smart-type), or selects a feasible strategy as in a Nash game (regular-type). We model the problem as two Bayesian games. In the first game, the user has incomplete information about the jammer, and in the second game, the jammer has incomplete information about the user. The user's utility is throughput. We prove that a unique equilibrium exists and derive it in closed form as a function of the known probabilities. We show that the Nash and Stackelberg equilibria are boundary cases of the obtained equilibrium. Thus, our approach allows one to incorporate the Nash and Stackelberg equilibria into a unified scale of equilibria. Monotonicity properties of the equilibrium strategies and the corresponding payoffs with respect to the network parameters are proven, and also supported by simulations.

Due to the shared and open-access nature of the wireless medium, wireless networks are vulnerable to jamming attacks. In this paper we study the problem of resource assigning in a single carrier communication system, where a user is communicating with a destination in the presence of a jammer. The jammer's channel to the destination is assumed flat fading, and its gain is known in probabilistic terms. In particular, the jammer's channel gain could take any value out of a finite set, with an a priori known probability. We model the problem in a Bayesian jamming game framework with utility the user throughput. We prove the existence and uniqueness of Nash and Stackelberg equilibria, and derive the equilibrium strategies in closed form. Our theoretical results, also supported by simulations, suggest that the Nash strategy is more sensitive to varying a priori probabilities, as compared to the Stackelberg strategy.

Wireless networks are susceptible to malicious attacks, especially those involving jamming and eavesdropping. To maintain secure and reliable communication under such threats, different anti-adversary strategies have been proposed to mitigate the adversary impact. In this paper, we consider a sophisticated adversary with the dual capability of either eavesdropping passively or jamming any ongoing transmission, and investigate a new aspect to consider when designing an anti-adversary strategy: how uncertainty about whether the rival is rational or subjective could impact the strategies. To model such uncertainty, we formulate a Bayesian Prospect Theory (BPT) extension of the game between a user and an adversary who chooses between an eavesdropping attack and a jamming attack against the user. Meanwhile the user chooses against which of the threats to apply the corresponding best response strategy. Uniqueness of the BPT equilibrium strategies is proven and they are found in closed form.

Graph theoretical analysis is a powerful tool for quantitatively evaluating brain connectivity networks. Conventionally, brain connectivity is assumed to be temporally stationary, whereas increasing evidence suggests that functional connectivity exhibits temporal variations during dynamic brain activity. Although a number of methods have been developed to estimate time-dependent brain connectivity, there is a paucity of studies examining the utility of brain dynamics for assessing brain disease states. Therefore, this paper aims to assess brain connectivity dynamics in Parkinson's disease (PD) and determine the utility of such dynamic graph measures as potential components to an imaging biomarker. Resting-state functional magnetic resonance imaging data were collected from 29 healthy controls and 69 PD subjects. Time-varying functional connectivity was first estimated using a sliding windowed sparse inverse covariance matrix. Then, a collection of graph measures, including the Fiedler value, were computed and the dynamics of the graph measures were investigated. The results demonstrated that PD subjects had a lower variability in the Fiedler value, modularity, and global efficiency, indicating both abnormal dynamic global integration and local segregation of brain networks in PD. Autoregressive models fitted to the dynamic graph measures suggested that Fiedler value, characteristic path length, global efficiency, and modularity were all less deterministic in PD. With canonical correlation analysis, the altered dynamics of functional connectivity networks, and particularly dynamic Fiedler value, were shown to be related with disease severity and other clinical variables including age. Similarly, Fiedler value was the most important feature for classification. Collectively, our findings demonstrate altered dynamic graph properties, and in particular the Fiedler value, provide an additional dimension upon which to non-invasively and quantitatively assess PD.

Ensuring confidentiality of communication is fundamental to securing the operation of a wireless system, where eavesdropping is easily facilitated by the broadcast nature of the wireless medium. By applying distributed beamforming among a coalition, we show that a new approach for assuring physical layer secrecy, without requiring any knowledge about the eavesdropper or injecting any additional cover noise, is possible if the transmitters frequently perturb their phases around the proper alignment phase while transmitting messages. This approach is readily applied to amplitude-based modulation schemes, such as PAM or QAM. We present our secrecy mechanisms, prove several important secrecy properties, and develop a practical secret communication system design. We further implement and deploy a prototype that consists of 16 distributed transmitters using USRP N210s in a 20×20×3m3area. By sending more than 160M bits over our system to the receiver, depending on system parameter settings, we measure that the eavesdroppers failed to decode 30%-60% of the bits cross multiple locations while the intended receiver has an estimated bit error ratio of 3×10-6.

Due to the shared and open-access nature of the wireless medium, wireless networks are vulnerable to interference in the form of jamming attacks. In the research literature, game theory is a commonly employed tool to describe such jammming attacks as well as to design anti-jamming (defense) strategies. An advantage of such an approach is that it allows one to consider the adversary as a smart agent, who flexibly responds to the action of the other agents. In this paper, we put forward a question: what happen if the rival is smart? How does a priori knowledge about this impact on the rivals strategies. We formulate a jamming problem in a CDMA-style network as a Bayesian game between a jammer and a user with two-sided incomplete information about the type of rival it faces. We prove that the equilibrium exists and is unique. Closed form criteria to establish whether the equilibrium is an inner or boundary equilibrium is established. We derive monotonicity properties for the superposition of the two best response strategies, which allows us to develop an algorithm based on the bisection method to find the fixed point (i.e. equilibrium) of this superposition of best response strategies. Our algorithm can be considered as a learning algorithm since it allows to reduce the zone of uncertainty for the equilibrium by a half per iteration.

Unutilized spectrum, i.e. spectrum holes, are opportunities that may be used for communication or other RF services. In this paper, we explore adversarial attacks that reduce the size of spectrum holes by showing their advantage compared to a random jammer. Using a game-theoretical approach, we design an optimal scanning strategy that provides an increased probability of detecting such an attack. The advantage of our strategy is achieved by focusing scanning efforts on bands that are more likely to be attacked, and neglecting the others. However, such focused scanning is a disadvantage since, if the adversary has a different objective, he can safely sneak usage of the bands neglected by such a specially-tuned spectrum scanner. To deal with this problem, we also derive the optimal scanning allocation that balances between applying the anti-spectrum holes attack scanning strategy and scanning the neglected bands so as to prevent the possibility of the adversary using those bands without being detected.

The problem of ensuring the secrecy of a communication while simultaneously maintaining sufficient throughput is a fundamental challenge facing secret communication. One of the challenges for such problems is that the optimal solution for one of objective might be not optimal for the other (e.g., an increase in secrecy might yield a decrease in throughput). Thus, there is a need for finding a trade-off solution for these objectives. In this paper, we consider a two-step approach to solve such problems and illustrate it for orthogonal frequency-division multiplexing-style communications. In the first step, we use the α-fairness criteria for formulating the tradeoff between objectives. A generalized water-filling equation for this tradeoff problem is solved. This equation includes, as a limit case, the classical case for secret communication with secrecy capacity as payoff. In the second step, we aim to find the best α-fair strategy, and show that Jain's fairness can potentially lead to an unbalanced tradeoff between the two objectives. We arrive at a more balanced tradeoff by means of bargaining over the continuum of α-fair solutions. Both the Nash and Kalai-Smorodinsky bargaining solutions for fulfillment of both objectives are found, and the algorithms for finding the bargaining solutions are derived.

Unutilized spectra, i.e., spectrum holes, are opportunities that may be used for communication or adapting other services that use radio frequency (RF). Such opportunities can also represent an adversarial target, if his objective is to block the RF system from using such opportunities opened by spectrum holes. In this paper, we explore the challenge of finding spectrum holes in an adversarial environment.First, by means of a simple model, we show that an adversary’s attack designed to close spectrum holes can be more harmful for the spectrum holes than just random jamming. This calls for designing a scanning strategy to detect such an attack.Second, by applying a game-theoretical model, we design the optimal scanning strategy to detect such attacks. In particular, we show the efficiency of such a scanning strategy compared with uninformed random scanning. This efficiency is achieved by focusing scanning efforts on the bands that will be more likely under attack, and neglecting less promising bands. Beyond the benefits, though, such a strategy has also drawbacks since, if the adversary has a different objective, such as sneaking usage of the spectrum, he can sneak usage undetected by using the bands neglected by such specially tuned scanning. To deal with this problem,third, we suggest to combine this strategy with a strategy that maximizes detection probability in a learning algorithm that updates the beliefs about the adversary’s objective. The convergence of the combined algorithm is proven.

This paper focuses on the challenge of maintaining reliable connectivity in an ad hoc network, where interference is possible. To cope with such interference, the paper introduces throughput connectivity and weighted throughput connectivity. Throughput connectivity reflects the possibility of establishing communication between nodes for given a signal power level, while weighted throughput connectivity associates the throughput as a weight in the associated network graph. Throughput connectivity is less sensitive to network's parameters than the one based on weighted throughput connectivity. It makes maintaining throughput connectivity protocol less resource consuming (say, by sending less frequently channel state information (CSI)). Whereas, weighted throughput protocol is more efficient in power allocation due to employing a continuous scale in Laplacian matrix. To illustrate these notions, two approaches to maximize connectivity were considered: (a) an adaptive transmission protocol that re-allocates transmission power between nodes, and (b) detecting and eliminating a malicious threat to maintain accumulated connectivity over time slots. The first problem was modeled by a maxmin problem, and solved by Semi-Definite Programming. The second problem was modeled by a stochastic game and solved explicitly.

Heartbeat monitoring during sleep is critically important to ensuring the well-being of many people, ranging from patients to elderly. Technologies that support heartbeat monitoring should be unobtrusive, and thus solutions that are accurate and can be easily applied to existing beds is an important need that has been unfulfilled. We tackle the challenge of accurate, low-cost and easy to deploy heartbeat monitoring by investigating whether off-the- shelf analog geophone sensors can be used to detect heartbeats when installed under a bed. Geophones have the desirable property of being insensitive to lower-frequency movements, which lends itself to heartbeat monitoring as the heartbeat signal has harmonic frequencies that are easily captured by the geophone. At the same time, lower-frequency movements such as respiration, can be naturally filtered out by the geophone. With carefully-designed signal processing algorithms, we show it is possible to detect and extract heartbeats in the presence of environmental noise and other body movements a person may have during sleep. We have built a prototype sensor and conducted detailed experiments that involve 43 subjects (with IRB approval), which demonstrate that the geophone sensor is a compelling solution to long-term at-home heartbeat monitoring. We compared the average heartbeat rate estimated by our prototype and that reported by a pulse oximeter. The results revealed that the average error rate is around 1.30% over 500 data samples when the subjects were still on the bed, and 3.87% over 300 data samples when the subjects had different types of body movements while lying on the bed. We also deployed the prototype in the homes of 9 subjects for a total of 25 nights, and found that the average estimation error rate was 8.25% over more than 181 hours' data.

Abstract Because of the open access nature of wireless communications, wireless networks can suffer from malicious activity, such as jamming attacks, aimed at undermining the network's ability to sustain communication links and acceptable throughput. One important consideration when designing networks is to appropriately tune the network topology and its connectivity so as to support the communication needs of those participating in the network. This paper examines the problem of interference attacks that are intended to harm connectivity and throughput, and illustrates the method of mapping network performance parameters into the metric of topographic connectivity. Specifically, this paper arrives at anti‐jamming strategies aimed at coping with interference attacks through a unified stochastic game. In such a framework, an entity trying to protect a network faces a dilemma: (i) the underlying motivations for the adversary can be quite varied, which depends largely on the network's characteristics such as power and distance; (ii) the metrics for such an attack can be incomparable (e.g., network connectivity and total throughput). To deal with the problem of such incomparable metrics, this paper proposes using the attack's expected duration as a unifying metric to compare distinct attack metrics because a longer‐duration of unsuccessful attack assumes a higher cost. Based on this common metric, a mechanism of maxmin selection for an attack prevention strategy is suggested. Copyright © 2017 John Wiley & Sons, Ltd.

Abstract Mobile ad hoc networks face many challenges when they are deployed, particularly problems associated with security and network failures arising from the dynamics of their network topologies. To address these issues, there have been many efforts to introduce security into the actual network protocols, most of which unfortunately struggle with the trade‐off between security and network overhead. Consequently, it is often desirable to have a lightweight approach to introduce security and robustness, where one employs conventional and well‐understood network protocols, and attempts to achieve the assurability of the network through higher‐layer, overlay mechanisms. This paper explores a lightweight overlay tunneling scheme operating at the Internet protocol layer as a policy tool that can mitigate network failures and attacks directed at the network without involving the redesign of the underlying routing protocols. Moreover, two optimizations are proposed that lead to improved performance when additional information is available. Copyright © 2016 John Wiley & Sons, Ltd.

When an adversary illicitly uses spectrum that it is not authorized for, it does so with a purpose in mind, such as to download a file or perhaps engage in a real-time communication session. In this paper, we examine how the incorporation of knowledge related to an adversary's purpose can improve the effectiveness of spectrum scanning protocols. First, we study the difference in the thief's behavior when considering throughput and delay as the two primary QoS parameters he is concerned with. Through our analysis, we show that the detection probability of unlicensed access to spectrum resources depends on the application type. Knowledge of the application type can be incorporated to spectrum scanning to tune better it to detect the thief. To illustrate this, we examine two Bayesian games. In the first game, the scanner wants to minimize the time needed to detect the invader. In the second game, the scanner wants to maximize the detection probability at each time slot by adapting its belief regarding the adversary's activity. In particular, it is shown in the minimizing detection time game that the equilibrium strategies are continuous with respect to priori knowledge of the invader's activity. Meanwhile, for the maximizing detection probability game, the strategies can have a jump discontinuity. This phenomena can be explained as the difference between tactical and strategic decision making: tactical decision making allows short-term, unpredictable moves, while strategic decision making is inclined to predictable moves. Finally, since the bandwidth model used in this paper is general, the conclusion as well as the approach provided can be applied to a variety of different network protection problems.

We propose a distributed access point selection scheme by which nodes select an appropriate access point to associate with based upon each individual device's channel utilization. In this paper, we define channel utilization as the ratio of required bandwidth to estimated available bandwidth. By incorporating channel utilization into the access point selection protocol, we can effectively reduce unnecessary reassociations and improve upper layer performance such as throughput and packet delivery delay. We have further enhanced our association protocol by using reinforcement learning to dynamically schedule the probing of neighboring access points (APs), ultimately bringing down the probing overhead by learning from past experience. When channel utilization is combined with adaptive probing, we observe a significant performance improvement compared to traditional association approaches.

Detecting malicious users in dynamic spectrum access scenarios is a crucial problem that requires an intrusion detection system (IDS) that scans spectrum for malicious activities. In this paper we design a spectrum scanning protocol that incorporates knowledge about the scanning effectiveness across different bands, which can increase scanning efficiency. The adversary, however, can also exploit such knowledge to its advantage. To understand the interplay underlying this problem, we formulate a Bayesian model, where the IDS faces a scanning allocation dilemma: if the intruder has no knowledge, then all the bands are under equal threat, while if the intruder has complete knowledge, then less-protected bands are more likely to be threatened. We solve this dilemma and show the optimal IDS strategy switches between the optimal response to these threats. Finally, we show that the strategy might be sensitive to prior knowledge, which can be corrected by adapted learning.

Jamming attacks are a class of network denial of service attacks that can easily be carried out in wireless networks. In order to be able to repair a network in the presence of such attacks, it is desirable to identify the location of jammed nodes and the congested area that is affected by the jammer. In this paper, we propose the design of a Q-learning based attack-localization algorithm that is integrated with the OLSR routing protocol. Our Q-learning attack-localization algorithm is distributed, asynchronous and can identify the location of the jammer in run-time as the attack takes place. We examine the performance of our approach using NS3 network simulations under two different network topologies, and for both naive and intelligent attack scenarios.

The reliable coordination of communication channels between two organizations is becoming an increasingly important problem as we move toward cognitive radio systems that support dynamic spectrum access. The benefit of such coordination is clear in scenarios when both participants are completely benign, but such benefits can be easily negated if one of the participants operates in a manner contrary to their channel assignment. In this paper, we develop and explore a maxmin transmission protocol for a primary user (PU) in a multiband wireless network, where the secondary user (SU) may be malicious and have an intent to cause interference. In this case, the threat that a SU may be an adversary changes the problem and places the PU in a dilemma: 1) if the SU is an adversary then to decrease the probability of interference it is better for the PU to select which channels it uses from a larger set of bands (i.e., possibly even including the bands reserved for the SU) and 2) if the SU turns out to be law obedient, then using a larger set of bands leads to an increased chance of being interfered with. Similarly, the SU also faces a dilemma if he is malicious: if the PU thinks that the SU is law obedient, then to increase the probability of jamming, the SU should target only the bands reserved for the PU; while, if the PU thinks that the SU is malicious, then by switching to the bands reserved for the SU, the probability of interference can be significantly or even totally reduced. Using game-theoretical tools, we formally explore these dilemmas and use the resulting analysis to explore the tradeoffs between different strategies in terms of payoffs to each user and knowledge of the SU's characteristics.

Overlay networks are a beneficial approach to designing robust and specialized networks on top of the generic IP architecture, and have been applied to the operation of mesh and mobile ad hoc networks. Unfortunately, when routing between entities in the overlay, inefficiencies are incurred due to potential ``back tracking'' that arises because of the discrepancies between the overlay and underlay topologies. In this paper, we minimize the ``back tracking'' problem by applying physical contexts shared by the network layer with the overlay so as to efficiently guide application flow. We have devised an intelligent cluster head and path selection algorithm for our overlay routing and compared its performance with the popular Chord protocol and a baseline AODV routing protocol. Simulation results indicate that: 1) the integration between logical and physical routing gives a large improvement in the number of hops for each transmission path; and 2) the selection of a good cluster head has only a moderate increase in transmission time.

We consider the game where Alice wants to communicate with Bob secretely, while Eve wants to hinder this objective by either eavesdropping or jamming, though she cannot employ both eavesdropping and jamming simultaneously. Alice is employing a multi-channel communication scheme, such as OFDM, and can control the transmit power allocation of her signal among the channels. If Eve chooses to jam, she can control her jamming power allocation amongst the channels, but in this case cannot eavesdrop. In this paper we examine three different patterns for Alice's (and Eve's) behavior: (a) Alice assumes Eve employs either a pure jamming or eavesdropping strategy and determines her optimal mixed strategy under this assumption; (b) assuming a fixed probability with which Eve will jam/eavesdrop, Alice/Eve's equilibrium power allocation strategies can be determined, and then Eve chooses the probability that maximizes her payoff; (c) Eve chooses between two modes (either to jam or eavesdrop) as well as power allocations simultaneous with Alice's selection of power allocation. Using a game-theoretic formulation, the equilibrium strategies are found for each model and conditions where players apply mixed strategies are produced.

A recent trend in clean-slate network design has been to separate the role of identifiers from network locators. An essential component to such a separation is the ability to resolve names into network addresses. One challenge facing name resolution is securing the name resolution service. This paper examines the security of a clean-slate name resolution service suitable for mobile networking. We begin with a high- level threat analysis, and identify several types of attacks that may be used against name resolution services. We then present secure protocols that together form a secure global name resolution service. Specifically, we present a secure update protocol that allows users to update their network addresses as they migrate and that includes several checkpoints that prevents spoofing, collusion, stale identifiers and false identifier announcements. Since the primary function behind a name resolution service is to respond to address-lookup queries, we also present a secure query protocol. Finally, we address the security risks associated with IP holes that can arise in a global name resolution service.

Radio frequency based device-free passive (DfP) localization techniques have shown great potentials in localizing individual human subjects, without requiring them to carry any radio devices. In this study, we extend the DfP technique to count and localize multiple subjects in indoor environments. To address the impact of multipath on indoor radio signals, we adopt a fingerprinting based approach to infer subject locations from observed signal strengths through profiling the environment. When multiple subjects are present, our objective is to use the profiling data collected by a single subject to count and localize multiple subjects without any extra effort. In order to address the non-linearity of the impact of multiple subjects, we propose a successive cancellation based algorithm to iteratively determine the number of subjects. We model indoor human trajectories as a state transition process, exploit indoor human mobility constraints and integrate all information into a conditional random field (CRF) to simultaneously localize multiple subjects. As a result, we call the proposed algorithm SCPL -- sequential counting, parallel localizing. We test SCPL with two different indoor settings, one with size 150 m2 and the other 400 m2. In each setting, we have four different subjects, walking around in the deployed areas, sometimes with overlapping trajectories. Through extensive experimental results, we show that SCPL can count the present subjects with 86% counting percentage when their trajectories are not completely overlapping. Our localization algorithms are also highly accurate, with an average localization error distance of 1.3 m.

Typically, a multipath channel response can be characterized as a sum of Rayleigh-fading ''rays'', each defined by a time delay and a mean-square amplitude. Therefore, the channel response can be largely described by a power delay profile (PDP), which is the set of mean-square ray amplitudes and relative delays. Here, we address the following question: Given an actual (or ''true'') PDP, PDP(τ), which may have many rays, is there a 3-ray (i.e. 3- tap) equivalent response, derivable from PDP(τ), that can be used to accurately estimate the average bit error rate,, vs. receiver input signal- to-noise ratio, SNR? The results reported here give an affirmative answer, e.g., forvalues down to = 10-4, the required SNR using a 3-tap equivalent channel response is less than 1.1 dB larger than that required for the ''true'' channel. This agreement can be improved upon, suggesting further work on deriving and evaluating equivalent 3-tap channels. We discuss the benefits of such simplifications for hardware emulators as well as for simulation and analysis.

Wireless spoofing attacks are easy to launch and can significantly impact the performance of networks. Although the identity of a node can be verified through cryptographic authentication, conventional security approaches are not always desirable because of their overhead requirements. In this paper, we propose to use spatial information, a physical property associated with each node, hard to falsify, and not reliant on cryptography, as the basis for 1) detecting spoofing attacks; 2) determining the number of attackers when multiple adversaries masquerading as the same node identity; and 3) localizing multiple adversaries. We propose to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. We then formulate the problem of determining the number of attackers as a multiclass detection problem. Cluster-based mechanisms are developed to determine the number of attackers. When the training data are available, we explore using the Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers. In addition, we developed an integrated detection and localization system that can localize the positions of multiple attackers. We evaluated our techniques through two testbeds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings. Our experimental results show that our proposed methods can achieve over 90 percent Hit Rate and Precision when determining the number of attackers. Our localization results using a representative set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries.

Dynamic spectrum access is a powerful approach to taking advantage of opportunities in spectrum to communicate. Access to these spectral opportunities should be regulated and monitored to prevent unapproved theft of spectral resources, which ultimately belong to a primary user. Unfortunately, most of the literature devoted to spectrum scanning does not consider the over-arching application that a spectrum thief might try to run. In this paper, we show that the thief's application (specifically, its QoS requirements), plays a critical role in how the thief should attempt to sneak spectrum and, consequently, a critical role in how the spectrum monitoring infrastructure should scan spectrum to detect thievery of spectral resources. We study the difference in the thief's behavior when considering bandwidth and delay as the two primary QoS parameters he is concerned with. Loosely speaking, this corresponds to sneaking for file-download versus streaming video, and the ultimate lesson learned is that the detection probability of unlicensed access to spectrum resources depends on the application type. As a consequence, knowledge of the application type allows for the primary user to improve spectrum scanning. Given the juxtaposition between the thief's and scanner's objectives, and the underlying dependency between detection and application QoS requirements, we finally formulate an adversarial Bayesian game where the scanner's scanning takes into account statistical knowledge about applications used by the user. The equilibrium strategies of this game are found in closed form what allowed to find their interesting properties. In particular, it was shown that the equilibrium sneaking strategies for different types of user are bandwidth-sharing, and we demonstrate how information about the application the user prefers to sneak at can improve the monitoring strategy.

Technological advancements have made it possible to use information associated with a mobile's location to form new computing and services. One concern with these emerging location-based services (LBS) is their ability to provide security while remaining reliable and accurate. In this paper, we focus on securing Mobile Location-based Services (MLBS), where certain goods or services are provided by mobile vendors to a clientele based on the proximity of vendors to potential customers. We identify different attacks and misuse faced by MLBS, and show that position verification is a critical step in providing a secure and trustworthy MLBS. To provide position verification, we propose a scheme called Key Distribution-based Position Verification (KEPI), which takes advantage of an auxiliary network of transponders to facilitate trustworthy location-based services. We derive an analytical model to evaluate our approach and our simulation results provide useful insights about how auxiliary networks can help provide trustworthy mobile services.

In this paper, we examine the problem of identifying different association protocols based on client probing patterns. We take the view point of an attacker, who aims to trick certain clients to switch their association to a compromised AP, so that the attacker can easily perform various attacks, such as passing false management frames and stealing client information. In order to do that, the attacker must know what association protocol the client is using since it determines the clients switching criteria. Therefore, the attacker must be able to identify the association protocol by monitoring the network traffic. We investigated methods to identify four association protocols and propose an approach which combines k-means clustering and Gaussian fitting to classify the association protocols based on probing patterns. We tested the designed scheme on traffic traces for a variety of network scenarios. We also designed a method to quantify the likelihood of the identification using confidence intervals. Results show that the proposed method can correctly identify association protocols. Further interpretation of the results also reveals information regarding important metrics of the clients chosen association protocol.

Multiple-input multiple-output (MIMO) technologies are a popular choice for emerging wireless systems due to their promised gains in throughput and reliability. In order to realize any gains over traditional non-MIMO communication systems, these systems must possess accurate knowledge of the wireless channel. In this paper, we investigate strategies for disrupting MIMO communications by developing attacks that target the often overlooked, but essential, channel estimation procedure. Our study focuses on the two most popular and well-known MIMO techniques: the capacity achieving SVD-based MIMO scheme, and the Alamouti space-time block code (STBC), which spans many protocols including 802.11n, WiMAX, and 3GPP. We augment theoretical and simulation results with real-world experimentation using the USRP/GNU Radio software defined radio platform. We also present novel methodology to protect the channel estimation procedure from such attacks by embedding authentication messages into physical layer features of the transmissions.

We describe a method for estimating achievable data rates in urban microcells using multiple-input/multiple-output (MIMO) techniques. Specifically, we use site maps and a versatile ray-tracing tool to compute MIMO gain matrices as a function of terminal location; and we use these matrices to determine achievable rates for various MIMO transmission modes (spatial multiplexing, beamforming, and diversity). Numerical results are generated for specific paths in Boston and Manhattan, though our results are shown to be fairly insensitive to neighborhood or city. We also show that, in urban microcells, data rate prediction using site-specific ray tracing is more informative than using stochastic models; and that adaptive switching among MIMO transmission modes as a terminal moves along its trajectory can help sustain high data rates. A new mode-switching algorithm is proposed that requires switching rates lower than those for the optimal scheme by a factor greater than 10, with little loss in average data rate. We also propose a novel software algorithm for optimally placing microcell bases. For a Manhattan neighborhood of area 0.5 km2, we find that full coverage can be obtained using only 5 bases, and that the highest total throughput is achieved using a frequency reuse factor of 1.

In this paper, we propose a distributed access point selection scheme by which nodes select an appropriate access point to associate with based on each individual device's channel utilization. We define channel utilization as the ratio of required bandwidth to estimated available bandwidth. By incorporating channel utilization into the access point association protocol, we can effectively reduce unnecessary reassociations and improve upper layer performance such as throughput and packet delivery delay. We have further enhanced our association protocol by using adaptive switching to schedule the switching to neighboring access points (APs), ultimately bringing down the association overhead. When channel utilization is combined with adaptive switching, we observe a significant performance improvement compared to traditional association approaches.

Forming secure associations between wireless devices that do not share a prior trust relationship is an important problem. This paper presents ProxiMate, a system that allows wireless devices in proximity to securely pair with one another autonomously by generating a common cryptographic key directly from their shared time-varying wireless environment. The shared key synthesized by ProxiMate can be used by the devices to authenticate each others' physical proximity and then to communicate confidentially. Unlike traditional pairing approaches such as Diffie-Hellman, ProxiMate is secure against a computationally unbounded adversary and its computational complexity is linear in the size of the key. We evaluate ProxiMate using an experimental prototype built using an open-source software-defined platform and demonstrate its effectiveness in generating common secret bits. We further show that it is possible to speed up secret key synthesis by monitoring multiple RF sources simultaneously or by shaking together the devices that need to be paired. Finally, we show that ProxiMate is resistant to even the most powerful attacker who controls the public RF source used by the legitimate devices for pairing.

Accurate channel estimation is essential to modern wireless communication. Pilot waveforms are susceptible to attacks that can severely degrade performance. Thus, it is important to protect channel estimation. Related research focuses on transmitter authentication rather than channel estimate authentication, and results rely heavily upon correlated estimates that occur within the channel coherence time in multipath-rich environments and/or sacrifice system throughput. We propose a methodology to authenticate channel estimation by leveraging physical layer properties of the wireless channel without any coherence time dependence or overhead. Our methods inherently provide data authentication, work in any environment, and provide error inference. We focus on general multi-antenna, multicarrier communication schemes and relate our results to existing protocols such as 802.11g/n and WiMAX.

Sniffing encrypted data packets traveling across networks can often be useful in inferring nontrivial information about their contents because of the manner in which the transmission of such packets is handled by lower layers in the communications protocol stack. In this paper, we formally study the side-channel formed by variable packet sizes, and explore obfuscation approaches to prevent information leakage while jointly considering the practical cost of obfuscation. We show that randomized algorithms for obfuscation perform best and can be studied as well-known information-theoretic constructs, such as discrete channels with and without memory. We envision a separate layer called a Bit - Trap, that employs buffering and bit-padding as orthogonal methods for obfuscating such side channels. For streams of packets, we introduce the use of mutual-information rate as an appropriate metric for the level of obfuscation that captures nonlinear relationships between original and modified streams. Using buffering-delay and average bit-padding as the respective costs, a Bit - Trap formulates a constrained optimization problem with bounds on the average costs, to implement the best possible obfuscation policy. We find that combining small amounts of delay and padding together can create much more obfuscation than either approach alone, and that a simple convex trade-off exists between buffering delay and padding for a given level of obfuscation.

The 31 papers in this special issue focus on using the physical layer for securing the next generation of communication systems.

In this paper, we introduce a delay-sensitive service that involves transmitting large amounts of location-based data to nodes at multiple locations. Given a limited amount of access points (APs) and an abundance of service requests that result from the nodes moving around, a typical content delivery service would inevitably introduce considerable delay. To solve this problem, we analyze the movement pattern of mobile nodes and approximate it as a semi-Markov process. Based on this model, we explore different components of the underlying service delay and propose that APs should use a multicast strategy to minimize the queuing delay component. Furthermore, we demonstrate the feasibility of employing nodes, which already have their own local copies of location-relevant data, to relay such data to other nodes by employing one or multiple communication channels. Lastly, we examine the resulting algorithms and study their performance relative to baseline content-delivery schemes through simulations.

We propose a PHY-authentication protocol to detect spoofing attacks in wireless networks, exploiting the rapid-decorrelation property of radio channels with distance. In this protocol, a PHY-authentication scheme that exploits channel estimations that already exist in most wireless systems, cooperates with any existing-either simple or advanced-higher-layer process, such as IEEE 802.11i. With little additional system overhead, our scheme reduces the workload of the higher-layer process, or provides some degree of spoofing protection for ``naked" wireless systems, such as some sensor networks. We describe the performance of our approach as a function of the spoofing pattern and the snapshot performance that can be easily measured through field tests. We discuss the implementation issues of the authentication protocol on 802.11 testbeds and verify its performance via field tests in a typical office building.

We present algorithms for adapting the MIMO transmission mode to varying channel conditions. Using real paths in Manhattan and Boston, we show that no single fixed transmission mode is superior to others over an entire path. Our two proposed switching algorithms, delayed feedback and probabilistic switching, achieve rates within 3% of the channel capacity. The delayed feedback algorithm requires less switching than the probabilistic switching algorithm. We compare the use of switching with the use of fixed mode transmissions over 50-m long paths. We show that 1) the use of switching rather than the best fixed mode gives at most a 9% gain in average data rate; and 2) the data rate gain relative to using the worst fixed mode can be as high as 90%. A very low rate switching (every 50 m) is thus attainable in theory but it is practical only if the best fixed mode can be accurately predicted.

Wireless devices are being developed that can scan spectrum to take advantage of spectrum opportunities for enhanced communication. For these devices to communicate better, it is desirable that they have an awareness of their setting. In this paper, we present a collection of techniques, which we call PLATEAU: Physical Layer Techniques for Enhanced Situational Awareness, which leverages physical layer properties from existing signals to gain an accurate picture of a device's environment as well as understanding of that device's mobility. We show through experiments using measurements from a software defined radio that, by utilizing radar and machine learning signal processing, a device can make more informed operational decisions.

Current link adaptation algorithms for IEEE 802.11 WLANs exhibit behavior which makes them unsuitable for transmission of multiple simultaneous real-time uplink video streams. First, these algorithms do not consider the properties of the video codec, and hence, are unaware of the impact of PHY rate selection on the perceptual quality of the received video. Second, they do not differentiate between channel errors and collisions, and hence severely malfunction when the collision probability is non-negligible. In this paper, we propose a link adaptation strategy that not only optimizes the perceptual quality of the received video, but also maintains network stability by preventing catastrophic failure due to collisions. We show that switching to a lower PHY rate improves the SNR/BER performance, but increases channel contention (and hence the collision probability). Then, we use this information plus knowledge of the video codec and network transport protocol to estimate the received perceptual video quality at the current and adjacent PHY rates. The PHY rate that yields the best perceptual quality is chosen for each Group of Pictures (GOP). We support the proposed algorithm through experiments with real wireless cameras on which we have implemented our algorithm.

Urban street-parking availability statistics are challenging to obtain in real-time but would greatly benefit society by reducing traffic congestion. In this paper we present the design, implementation and evaluation of ParkNet, a mobile system comprising vehicles that collect parking space occupancy information while driving by. Each ParkNet vehicle is equipped with a GPS receiver and a passenger-side-facing ultrasonic range-finder to determine parking spot occupancy. The data is aggregated at a central server, which builds a real-time map of parking availability and could provide this information to clients that query the system in search of parking. Creating a spot-accurate map of parking availability challenges GPS location accuracy limits. To address this need, we have devised an environmental fingerprinting approach to achieve improved location accuracy. Based on 500 miles of road-side parking data collected over 2 months, we found that parking spot counts are 95% accurate and occupancy maps can achieve over 90% accuracy. Finally, we quantify the amount of sensors needed to provide adequate coverage in a city. Using extensive GPS traces from over 500 San Francisco taxicabs, we show that if ParkNet were deployed in city taxicabs, the resulting mobile sensors would provide adequate coverage and be more cost-effective by an estimated factor of roughly 10-15 when compared to a sensor network with a dedicated sensor at every parking space, as is currently being tested in San Francisco.

Multiple-input multiple-output (MIMO) technologies are popular in emerging wireless systems. Optimal MIMO communication is achieved by applying a waterfilling solution over the parallel subchannels associated with the channel matrix between a transmitter and receiver. The viability of such a method relies on the transmitter and receiver performing the singular value decomposition (SVD) of the estimated channel matrix. The estimation and use of the estimated channel matrix, however, is a point of weakness that can be used to subvert MIMO communication. In this paper, we investigate strategies for disrupting MIMO communications by developing attacks that target the channel estimation procedure of a MIMO system. Specifically, we study the impact that jamming the channel estimation procedure can have on SVD-based MIMO systems. Further, most new standards that employ MIMO incorporate space-time block coding (STBC) to bolster throughput and reliability. Although the choice of STBC varies across the standards, the Alamouti [5] scheme is a common basis for many protocols, including 802.11n, WiMAX, and 3GPP. We present jamming attacks that target the Alamouti scheme, and support their validity and effectiveness in the real world using the USRP/GNU Radio platform.

Malicious users may reprogram cognitive radios to disregard how their actions may harm other users. To cope with such threats, we propose that cognitive radios must have a trusted domain, which contains an onboard regulation mechanism (ORM) that 'regulates' the radio's behavior by monitoring the radio, and taking appropriate action. We present a scheme for monitoring the link quality, in real-time to assess the proper action to take. Our method promptly prevents misbehavior by taking action in a manner proportional to the level by which the cognitive radio deviates from normal, allowed behavior. We demonstrate a method for the ORM to collect the link state information needed to regulate its cognitive radio. Lastly, we examine the resulting algorithms and study our regulation relative to traditional CSMA and Aloha MAC protocols on the ORBIT testbed using USRP/GNU Radios.

The multipath-rich wireless environment associated with typical wireless usage scenarios is characterized by a fading channel response that is time-varying, location-sensitive, and uniquely shared by a given transmitter-receiver pair. The complexity associated with a richly scattering environment implies that the short-term fading process is inherently hard to predict and best modeled stochastically, with rapid decorrelation properties in space, time, and frequency. In this paper, we demonstrate how the channel state between a wireless transmitter and receiver can be used as the basis for building practical secret key generation protocols between two entities. We begin by presenting a scheme based on level crossings of the fading process, which is well-suited for the Rayleigh and Rician fading models associated with a richly scattering environment. Our level crossing algorithm is simple, and incorporates a self-authenticating mechanism to prevent adversarial manipulation of message exchanges during the protocol. Since the level crossing algorithm is best suited for fading processes that exhibit symmetry in their underlying distribution, we present a second and more powerful approach that is suited for more general channel state distributions. This second approach is motivated by observations from quantizing jointly Gaussian processes, but exploits empirical measurements to set quantization boundaries and a heuristic log likelihood ratio estimate to achieve an improved secret key generation rate. We validate both proposed protocols through experimentations using a customized 802.11a platform, and show for the typical WiFi channel that reliable secret key establishment can be accomplished at rates on the order of 10 b/s.

Wireless sensor networks are typically deployed to monitor phenomena that vary over the spatial region the sensor network covers. The sensor readings may also be dual-used for additional purposes. In this paper, we propose to use the inherent spatial variability in physical phenomena, such as temperature or ambient acoustic energy, to support localization and position verification. We first present the problem of localization using general spatial information fields, and then, propose a theory for exploiting this spatial variability for localization. Our Spatial Correlation Weighting Mechanism (SCWM) uses spatial correlation across different phenomena to isolate an appropriate subset of environmental parameters for better location accuracy. We then develop an array of algorithms employing environmental parameters using a two-level approach: first, we develop the strategies on how the subset of parameters should be chosen, and second, we derive mapping functions for position estimation. Our algorithms support our theoretical model for performing localization utilizing environmental properties. Finally, we provide an experimental evaluation of our approach by using a collection of physical phenomena measured across 100 locations inside a building. Our results provide strong evidence of the viability of using general sensor readings for location-aware applications.

We consider a secret communication scenario where Alice wants to transmit secretly to Bob in presence of a passive eavesdropper Eve. The Alice-Bob channel is a fixed-SNR AWGN channel, while the Alice-Eve channel is a fast Rayleigh fading channel, with the channel states only known to Eve. Alice knows the statistics of Alice-Eve channel, but not the exact realizations. We investigate the achievable secrecy rates for this channel model with Gaussian signaling and discrete signaling. For Gaussian signaling, several transmission strategies according to the main channel's relative channel gain are proposed and evaluated. For discrete signaling, achievable secrecy rates with Quadrature Amplitude Modulation (QAM) are evaluated. When Bob's channel is much better than Eve's channel, simple Gaussian signaling can perform close to the upper bound, and is better than the rate achieved with M-QAM. When Bob's channel gain is on average worse than the eavesdropper's average channel gain, positive secrecy rate can still be achieved for Gaussian signaling with artificial noise injection and a burst signaling strategy. Moreover, M-QAM can outperform Gaussian signaling. The key factor that enables secret communication in this case is that both M-QAM and artificial noise limit the leakage of information when Eve's channel is unusually good.

Wireless networks are vulnerable to identity spoofing attacks, where an attacker can forge the MAC address of his wireless device to assume the identity of another victim device on the network. Identity spoofing allows an attacker to avail network services that are normally restricted to legitimate users. Prior techniques to detect such attacks rely on characteristics such as progressions of MAC sequence numbers. However, these techniques can wrongly classify benign flows as malicious with newer 802.11e wireless devices that allow multiple progressions of MAC sequence numbers from the same device. Several other techniques that rely on physical properties of transmitting devices are ineffective when the attacker and the victim are mobile. In this paper, we propose an architecture to robustly detect identity spoofing attacks under varying operating conditions. Our architecture employs a series of increasingly powerful detectors to identify or eliminate the possibility of an attack, culminating in a powerful, RSSI-based per-packet localizer that reliably detects identity spoofing attacks. We implemented this architecture and used it to detect a variety of identity spoofing attacks. Our experiments show that it can effectively detect identity spoofs with a low false positive rate of 0.5%.

Several proposals on P2P-ISP cooperation have recently been developed using information sharing for locality-based peering. Their benefits in terms of P2P efficiency, ISP cost, and traffic localization have been demonstrated in the single ISP case. However, potential risks associated with such cooperation have not been well examined. This paper develops a taxonomy and a mathematical model to explore the unintended and counter-intuitive behaviors emerging out of these cooperations in the multiple ISP case. Through both numerical examples and analytical results, we illustrate how such behaviors may become damaging to both P2P providers and ISPs, and how they might be mitigated so that the full benefit of cooperation can be maintained.

Dynamic spectrum access has been proposed as a means to share scarce radio resources, and requires devices to follow protocols that use resources in a proper, disciplined manner. For a cognitive radio network to achieve this goal, spectrum policies and the ability to enforce them are necessary. Detection of an unauthorized (anomalous) usage is one of the critical issues in spectrum etiquette enforcement. In this paper, we present a network structure for dynamic spectrum access and formulate the anomalous usage detection problem using statistical significance testing. The detection problem is classified into two subproblems. For the case where no authorized signal is present, we describe the existing cooperative sensing schemes and investigate the impact of signal path loss on their performance. For the case where an authorized signal is present, we propose three methods that detect anomalous transmissions by making use of the characteristics of radio propagation. Analytical models are formulated for two special cases and, due to the intractability of the general problem, we present an algorithm using machine learning techniques to solve the general case. Our simulation results show that our approaches can effectively detect unauthorized spectrum usage with high detection rate and low false positive rate.

Wireless spoofing attacks are easy to launch and can significantly impact the performance of networks. Although the identity of a node can be verified through cryptographic authentication, conventional security approaches are not always desirable because of their overhead requirements. In this paper, we propose to use location information, a physical property associated with each node, hard to falsify, and not reliant on cryptography, as the basis for (1) detecting spoofing attacks; (2) determining the number of attackers when multiple adversaries masquerading as a same node identity; and (3) localizing multiple adversaries. We formulate the problem of determining the number of attackers as a multi-class detection problem. We first propose two cluster-based mechanisms to determine the number of attackers. We then develop SILENCE that employs the minimum distance testing of RSS values in addition to cluster analysis and can achieve better accuracy than other methods under study that merely use cluster analysis alone. We further developed an integrated detection and localization system that can localize the positions of multiple attackers. We evaluated our techniques through two testbeds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings. Our experimental results show that SILENCE can achieve over 90% Hit Rate and Precision when determining the number of attackers. Additionally, our localization results using a representative set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries.

Asset tracking is an important application domain for wireless sensor networks. However, continuous tracking of a large number of items at the individual item level over a significant period of time is still not feasible. There are two main obstacles. The first is the need for efficient, low-power communication protocols. Many current protocols employ energy-expensive methods to achieve reliable communication for arbitrary traffic situations. Such protocols are not suitable for continuous asset tracking applications. The second challenge is the lack of a robust presence detection algorithm that can differentiate packet losses caused by a missing item from packet losses caused by the ambient radio environment. In this paper, we designed a simple communication protocol, Uni-HB, and demonstrated it can lead to longer system lifetime and higher communication reliability than several popular protocols. We also devised two robust detection algorithms that can yield low false alarm rates while achieving timely loss notification. We took an experimental approach, and evaluated protocols on a generic embedded hardware platform that has an similar architecture to motes. We also derived analytical models to validate our experimental measurements.

The flexibility and openness of wireless networks enables an adversary to masquerade as other devices easily. Identity-based spoofing attacks are serious network threats as they can facilitate a variety of advanced attacks to undermine the normal operation of networks. However, the existing mechanisms can only detect spoofing attacks when the victim node and the spoofing node are static. In this paper, we propose a method for detecting spoofing attacks in the mobile wireless environment, that is when wireless devices, such as the victim node and/or the spoofing node are moving. We develop the DEMOTE system, which exploits received signal strength (RSS) traces collected over time and achieves an optimal threshold to partition the RSS traces into classes for attack detection. Further, our novel algorithm alignment prediction (ALP), when without the knowledge of spatial constraint of the wireless nodes, utilizes temporal constraints to predict the best RSS alignment of partitioned RSS classes for RSS trace reconstruction over time. Our approach does not require any changes or cooperation from wireless devices other than packet transmissions. Through experiments from an office building environment, we show that DEMOTE achieves accurate attack detection both in signal space as well as in physical space using localization and is generic across different technologies including IEEE 802.11 b/g and IEEE 802.15.4.

Abstract Multi‐hop routing is essential to the operation of wirelessad hocnetworks. Unfortunately, it is very easy for an adversary to forge or modify routing messages to inflict severe damage on the underlying routing protocol. In this paper, we present SEAR, a secure efficientad hocrouting (SEAR) protocol forad hocnetworks that is mainly based on efficient symmetric cryptography, with asymmetric cryptography used only for the distribution of initial key commitments. SEAR uses one‐way hash functions to protect the propagation of the routing messages. Intermediate nodes verify the routing messages by applying one‐way functions, while malicious nodes cannot construct beneficial false routing messages when forwarding them. Route error (RERR) messages are protected through a variation of the TESLA broadcast authentication scheme. The SEAR protocol does not require any additional routing packet formats, and thus follows the same basic design asad hocon‐demand distance vector (AODV). We show, through both theoretical examination and simulations, that SEAR provides better security with significantly less overhead than other existing secure AODV (SAODV) protocols. Copyright © 2008 John Wiley & Sons, Ltd.

Due to the broadcast nature of the wireless medium, wireless networks are especially vulnerable to Sybil attacks, where a malicious node illegitimately claims a large number of identities and thus depletes system resources. We propose an enhanced physical-layer authentication scheme to detect Sybil attacks, exploiting the spatial variability of radio channels in environments with rich scattering, as is typical in indoor and urban environments. We build a hypothesis test to detect Sybil clients for both wideband and narrowband wireless systems, such as WiFi and WiMax systems. Based on the existing channel estimation mechanisms, our method can be easily implemented with low overhead, either independently or combined with other physical-layer security methods, e.g.,spoofingattack detection. The performance of our Sybil detector is verified, via both a propagation modeling software and field measurements using a vector network analyzer, for typical indoor environments. Our evaluation examines numerous combinations of system parameters, including bandwidth, signal power, number of channel estimates, number of total clients, number of Sybil clients, and number of access points. For instance, both the false alarm rate and the miss rate of Sybil attacks are usually below 0.01, with three tones, pilot power of 10 mW, and a system bandwidth of 20 MHz.

Recently, it has been noted that localization algorithms that use signal strength are susceptible to noncryptographic attacks, which consequently threatens their viability for sensor applications. In this work, we examine several localization algorithms and evaluate their robustness to attacks where an adversary attenuates or amplifies the signal strength at one or more landmarks. We study both point-based and area-based methods that employ received signal strength for localization, and propose several performance metrics that quantify the estimator's precision, bias, and error, including Hölder metrics, which quantify the variability in position space for a given variability in signal strength space. We then conduct a trace-driven evaluation of a set of representative algorithms, where we measured their performance as we applied attacks on real data from two different buildings. We found the median error degraded gracefully, with a linear response as a function of the attack strength. We also found that area-based algorithms experienced a decrease and a spatial-shift in the returned area under attack, implying that precision increases though bias is introduced for these schemes. Additionally, we observed similar values for the average Hölder metric across most of the algorithms, thereby providing strong experimental evidence that nearly all the algorithms have similar average responses to signal strength attacks with the exception of the Bayesian Networks algorithm.

Although the content of sensor messages describing “events of interest” may be encrypted to provide confidentiality, the context surrounding these events may also be sensitive and therefore should be protected from eavesdroppers. An adversary armed with knowledge of the network deployment, routing algorithms, and the base-station (data sink) location can infer the temporal patterns of interesting events by merely monitoring the arrival of packets at the sink, thereby allowing the adversary to remotely track the spatio-temporal evolution of a sensed event. In this paper we introduce the problem of temporal privacy for delay-tolerant sensor networks, and propose adaptive buffering at intermediate nodes on the source-sink routing path to obfuscate temporal information from the adversary. We first present the effect of buffering on temporal privacy using an information-theoretic formulation, and then examine the effect that delaying packets has on buffer occupancy. We observe that temporal privacy and efficient buffer utilization are contrary objectives, and then present an adaptive buffering strategy that effectively manages these tradeoffs. Finally, we evaluate our privacy enhancement strategies using simulations, where privacy is quantified in terms of the adversary's mean square error.

We investigate the reliability of radio channel simulators in predicting channel responses throughout a well-specified environment. Indoor environments for which the geometric layout and material properties of surfaces are known lend themselves to such site-specific simulation. We assess the performance of this approach by comparing its predictions with measurements in a specific static environment. The good agreement on path loss, Ricean K-factor and RMS delay spread, over the set of paths measured and simulated, suggests that a well-designed radio simulator can be used reliably to predict system behavior. Typically, wireless channel models obtained through this or similar techniques do not capture the temporal variability in the channel response due to people movement in the environment. We treat the time-varying part of the channel response using stochastic processes. Using channel sounding experiments for several typical office scenarios, we show that autoregressive processes can be used to model the time-varying tap gains for several different motion scenarios.

The radio channel response decorrelates rapidly as the transmitter changes location in an environment with rich scatterers and reflectors. Based on this fact, a channel-based authentication scheme was previously proposed to discriminate between transmitters at different locations, and thus to detect spoofing attacks in wireless networks. In this paper, we study its application in frequency-selective Rayleigh channels, considering channel time variations due to environmental changes and terminal mobility, as well as the channel estimation errors due to the interference from other radios. We propose a generalized likelihood ratio test (GLRT) that is optimal but computationally cumbersome, and a simplified version that requires no a priori knowledge of channel parameters and is therefore more practical. We verify the efficacy of the channel-based spoofing detectors via numerical analysis, showing how performance is improved by using multiple antennas, higher transmit power, and wider system bandwidth. We show that, under a wide variety of practical conditions, spoofing can be detected with better than 90% probability while keeping the probability of falsely rejecting valid transmissions below 10%.

Multi-hop routing is essential to the operation of wireless ad hoc networks. Unfortunately, it is very easy for an adversary to forge or modify routing messages to inflict severe damage on the underlying routing protocol. In this paper, we present SEAR, a Secure Efficient Ad hoc Routing protocol for ad hoc networks that is mainly based on efficient symmetric cryptography, with asymmetric cryptography used only for the distribution of initial key commitments. We show, through both theoretical examination and simulations, that SEAR provides better security with significantly less overhead than other existing secure AODV protocols.

We investigate the reliability of radio channel simulators in capturing the important properties of radio channels throughout a well-specified environment. Indoor environments for which the geometric layout and material properties of surfaces are known lend themselves to such site-specific simulation. Our aim is to assess the performance of this approach by comparing its predictions with measurements in a specific environment. The measurements are made on 18 paths in the ORBIT Laboratory of Rutgers University's WINLAB; and the simulator we use is the WiSE ray-tracing tool developed by Bell Labs. The comparisons are made for three parameters that largely characterize a radio path's behavior: Path loss; Ricean K-factor; and RMS delay spread. The measurements are made over a 1-GHz bandwidth centered on 3.5 GHz. The comparisons show good agreement over the set of paths measured and simulated, establishing confidence that a well-designed radio simulator can be used reliably in system studies.

We propose an enhanced physical-layer authentication scheme for multi-carrier wireless systems, where transmission bursts consist of multiple frames. More specifically, it is based on the spatial variability characteristic of wireless channels, and able to work with moderate terminal mobility. For the authentication of the first frame in each data burst, the legal transmitter uses the saved channel response from the previous burst as the key for authentication of the first frame in the next burst. The key is obtained either via feedback from the receiver, or using the symmetric channel property of a TDD system. Then the authentication of the following frames in the burst is performed either by a Neyman-Pearson hypothesis test, or a least-squares adaptive channel estimator. Simulations in a typical indoor building show that the scheme based on the Neyman-Pearson test is more robust against terminal mobility, and is able to detect spoofing attacks efficiently with small system overhead when the terminal moves with a typical pedestrian speed.

In this paper, we investigate one of the major challenges in pervasive systems: energy efficiency, by exploring the design of an RFID system intended to support the simultaneous and real time monitoring of thousands of entities. These entities, which may be individuals or inventory items, each carry a lowpower transmit-only tag and are monitored by a collection of networked base-stations reporting to a central database. We have built a customized transmit-only tag with a small formfactor, and have implemented a real-time monitoring application intended to verify the presence of each tag in order to detect potential disappearance of a tag (perhaps due to item theft). Throughout the construction of our pervasive system, we have carefully engineered it for extended tag lifetime and reliable monitoring capabilities in the presence of packet collisions, while keeping the tags small and inexpensive. The major challenge in this architecture (called Roll-Call™) is to supply the energy needed for long range continuous tracking for a year or more while keeping the tags (called PIPs) small and inexpensive. We have used this as a model problem for optimizing cost, size and lifetime across the entire pervasive, persistent system from firmware to protocol.

We derive an outer bound for the secrecy capacity region of a class of one-sided interference channel. The transmitters are assumed to be trustworthy while the message is secure against the non-intended receiver. The outer bound is applied to a deterministic channel in which the outer bound is showed to be tight, and to a Gaussian one-sided interference channel where a scheme is proposed that can come within one bit of the outer bound.

This paper introduces an alternative communication scheme that can work as an overlay for existing commodity wireless devices and support communication when conventional communication is not possible. The methodology we propose provides a reliable communication link when presented with an unreliable environment (such as an urban canyon), or even when dealing with an adversary attempting to jam the receiver. The protocol we explore is a form of cooperative communication, where a team of radio teaming transmitters work together to relay messages by leveraging their multipaths in order to induce beam-pattern distortion at the intended receiver. This new form of cooperative communication differs from traditional approaches in that the typical stringent synchronization constraints of conventional beamforming and MIMO applications are relaxed, thereby making the protocol amenable to a team of heterogeneous wireless devices. We outline our communication scheme, and then validate it through simulations and an implementation using a current, real-world software defined radio (SDR) architecture - GNU radio and the universal software radio peripheral (USRP).

Wireless networks are vulnerable to sybil attacks, in which a sybil node forges multiple identifications to trick the system and conduct harmful attacks. The traditional approach to address sybil attacks is to employ cryptographic-related methods. However, conventional security approaches may not always desirable due to their infrastructural overhead. In this paper, we propose to utilize K-means cluster analysis for detecting sybil attacks based on the spatial correlation between the signal strength and physical locations. Our approach requires minimal overhead to wireless devices. We have evaluated our methods through experimentation using both an 802.11 (WiFi) network as well as an 802.15.4 (ZigBee) network in two office buildings. Our results show that the proposed sybil attack detector is highly effective with over 95% detection rates and under 5% false positive rates.

Securing communications requires the establishment of cryptographic keys, which is challenging in mobile scenarios where a key management infrastructure is not always present. In this paper, we present a protocol that allows two users to establish a common cryptographic key by exploiting special properties of the wireless channel: the underlying channel response between any two parties is unique and decorrelates rapidly in space. The established key can then be used to support security services (such as encryption) between two users. Our algorithm uses level-crossings and quantization to extract bits from correlated stochastic processes. The resulting protocol resists cryptanalysis by an eavesdropping adversary and a spoofing attack by an active adversary without requiring an authenticated channel, as is typically assumed in prior information-theoretic key establishment schemes. We evaluate our algorithm through theoretical and numerical studies, and provide validation through two complementary experimental studies. First, we use an 802.11 development platform with customized logic that extracts raw channel impulse response data from the preamble of a format-compliant 802.11a packet. We show that it is possible to practically achieve key establishment rates of ~ 1 bit/sec in a real, indoor wireless environment. To illustrate the generality of our method, we show that our approach is equally applicable to per-packet coarse signal strength measurements using off-the-shelf 802.11 hardware.

Wireless sensor networks monitor phenomena that vary over the spatial region the sensor network covers. The sensor readings may also be dual-used for additional purposes. In this paper we propose to use the inherent spatial variability in physical phenomena to support localization and position verification. We first present the problem of localization using general spatial information fields, and then propose a theory for exploiting this spatial variability for localization. Our spatio-correlation weighting mechanism (SCWM) uses spatial relationships of measured physical phenomena to determine an appropriate subset of environmental parameters for better location accuracy. We next present the Flex - EP algorithm, which supports our theoretical model for performing localization. Finally, we provide an experimental evaluation of our approach by using a collection of physical phenomena measured across one hundred locations inside a building. Our results provide strong evidence of the viability of using general sensor readings for location applications.

Wireless communication is susceptible to radio interference, which prevents the reception of communications. Although evasion strategies have been proposed, such strategies are costly or ineffective against broadband jammers. In this paper, we explore an alternative to evasion strategies that involves the establishment of a timing channel that exists in spite of the presence of jamming. The timing channel is built using failed packet reception times. We first show that it is possible to detect failed packet events inspite of jamming. We then explore single sender and multisender timing channel constructions that may be used to build a low-rate overlay link-layer. We discuss implementation issues that we have overcome in constructing such jamming-resistant timing channel, and present the results of validation efforts using the MICA2 platform. Finally, we examine additional error correction and authentication mechanisms that may be used to cope with adversaries that both jam and seek to corrupt our timing channel.

Abstract Vehicularad hocnetworks (VANETs) represent a promising new communication technology that can facilitate many new forms of automotive applications. Many of the applications that will run on these networks will require a high degree of security and privacy. In this paper, we present a robust and efficient security framework for vehicular networks suited for both inter‐vehicular and vehicle‐to‐infrastructure communication. Our system uses identity‐based cryptography (IBC) to provide authentication, confidentiality, non‐repudiation, and message integrity. It exploits the implicit authentication provided by IBC to significantly reduce the security/privacy‐related communication overhead. Additionally, it provides scalable, user‐customizable security and privacy using short‐lived, authenticated, and unforgeable, pseudonyms. This feature can be used by VANET applications that require quantifiable trust and privacy to provide differentiated service based on various levels of trust and privacy thresholds. Copyright © 2008 John Wiley & Sons, Ltd.

Location information should be verifiable in order to support new computing and information services. In this paper, we adapt the classical challenge-response method for authentication to the task of verifying an entity's location. Our scheme utilizes a collection of transmitters, and adapts the power allocations across these transmitters to verify a user's claimed location. This strategy, which we call a power-modulated challenge response, is able to be used with existing. wireless sensor networks. First, we propose a direct method, where some transmitters are selected to send ldquochallengesrdquo that the claimant node should be able to witness based on its claimed location, and for which the claimant node must correctly respond to in order to prove its location. Second, we reverse the strategy by presenting an indirect method, where some transmitters send challenges that the claimant node should not be able to witness. Then, we present a signal-strength-based method, where the node responds with its received signal strength and thereby provides improved location verification. To evaluate our schemes, we examine different adversarial models for the claimant, and characterize the performance of our power-modulated challenge response schemes under these adversarial models. Further, we propose a new localization attack, where a set of nodes collaborates to pretend that there is a node at the claimed location. This collusion attack can do tremendous harm to localization and the performance of the aforementined methods under collusion attack are explained. Finally, we propose the use of a rotational directional power-modulated challenge response, where directional antennas are used to defend against collusion attacks.

Radio interference, whether intentional or otherwise, represents a serious threat to assuring the availability of sensor network services. As such, techniques that enhance the reliability of sensor communications in the presence of radio interference are critical. In this article, we propose to cope with this threat through a technique called channel surfing, whereby the sensor nodes in the network adapt their channel assignments to restore network connectivity in the presence of interference. We explore two different approaches to channel surfing: coordinated channel switching, in which the entire sensor network adjusts its channel; and spectral multiplexing, in which nodes in a jammed region switch channels and nodes on the boundary of a jammed region act as radio relays between different spectral zones. For coordinated channel switching, we examine an autonomous strategy where each node detects the loss of its neighbors in order to initiate channel switching. To cope with latency issues in the autonomous strategy, we propose a broadcast-assisted channel switching strategy to more rapidly coordinate channel switching. For spectral multiplexing, we have devised both synchronous and asynchronous strategies to facilitate the scheduling of nodes in order to improve network fidelity when sensor nodes operate on multiple channels. In designing these algorithms, we have taken a system-oriented approach that has focused on exploring actual implementation issues under realistic network settings. We have implemented these proposed methods on a testbed of 30 Mica2 sensor nodes, and the experimental results show that channel surfing, in its various forms, is an effective technique for repairing network connectivity in the presence of radio interference, while not introducing significant performance-overhead.

It has been discussed in the literature that the mobility of a mobile sensor network (MSN) can be used to improve its sensing coverage. How the mobility can efficiently be managed toward a better coverage, however, remains unanswered. In this paper, motivated by classical dynamics that study the movement of objects, we propose the concept of network dynamics and define the associated potential functions that capture the operational goals, as well as the environment of an MSN. We find that in managing the mobility of an MSN, Newton's laws of motion in classical dynamics are insufficient, for they introduce oscillations into the movement of sensor nodes. Instead, in network dynamics, the laws of motion are formulated using the steepest descent method in optimization. Based on the network dynamics model, we first devise a parallel and distributed algorithm (parallel and distributed network dynamics (PDND)) that runs on each sensor node to guide its movement. PDND then turns sensor nodes into autonomous entities that are capable of adjusting their locations according to the operational goals and environmental changes. After that, we formally prove the convergence of PDND. Finally, we apply PDND in three applications to demonstrate its effectiveness.

The wireless medium contains domain-specific information that can be used to complement and enhance traditional security mechanisms. In this paper we propose ways to exploit the spatial variability of the radio channel response in a rich scattering environment, as is typical of indoor environments. Specifically, we describe a physical-layer authentication algorithm that utilizes channel probing and hypothesis testing to determine whether current and prior communication attempts are made by the same transmit terminal. In this way, legitimate users can be reliably authenticated and false users can be reliably detected. We analyze the ability of a receiver to discriminate between transmitters (users) according to their channel frequency responses. This work is based on a generalized channel response with both spatial and temporal variability, and considers correlations among the time, frequency and spatial domains. Simulation results, using the ray-tracing tool WiSE to generate the time-averaged response, verify the efficacy of the approach under realistic channel conditions, as well as its capability to work under unknown channel variations.

Current rate adaptation schemes for 802.11 exhibit sudden and severe drops in throughput in real application scenarios. Although there have been several propositions to remedy such rate adaptation failures, there has not been a thorough analysis of the causes that lead to such a "snowball effect." This paper provides an analysis of the factors that lead to the poor performance of current rate adaptation schemes in real environments. We show that current rate adaptation schemes fail because they do not differentiate between poor channel conditions and collisions as the source of transmission failures, and consequently invoke improper responses that cascade to dramatic throughput degradation. We support the analysis through experimentation with real data from a wireless video surveillance application, and provide recommendations for the next generation of WiFi rate control schemes.

Location information should be verifiable in order to support new computing and information services. In this paper, we adapt the classical challenge-response method for authentication to the task of verifying an entity's location. Our scheme utilizes a collection of transmitters, and adapts their power allocations to verify a user's claimed location. This strategy, which we call power-modulated challenge response, is able to be used with existing wireless sensor networks, and we present three variations. First, we propose a direct method, where some transmitters are selected to send "challenges" that the claimant node should be able to witness based on its claimed location, and for which the claimant node must correctly respond in order to prove its location. Second, we reverse the strategy by presenting an indirect method, where some transmitters send challenges that the claimant node should not be able to witness. Finally, we present a signal strength based method, where the node responds with its received signal strength and thereby provides improved location verification. To evaluate our schemes, we examine different adversarial models for the claimant, and characterize the performance of our power-modulated challenge response schemes under these adversarial models.

The wireless medium contains domain-specific information that can be used to complement and enhance traditional security mechanisms. In this paper we propose ways to exploit the fact that, in a typically rich scattering environment, the radio channel response decorrelates quite rapidly in space. Specifically, we describe a physical-layer algorithm that combines channel probing (M complex frequency response samples over a bandwidth W) with hypothesis testing to determine whether current and prior communication attempts are made by the same user (same channel response). In this way, legitimate users can be reliably authenticated and false users can be reliably detected. To evaluate the feasibility of our algorithm, we simulate spatially variable channel responses in real environments using the WiSE ray-tracing tool; and we analyze the ability of a receiver to discriminate between transmitters (users) based on their channel frequency responses in a given office environment. For several rooms in the extremities of the building we considered, we have confirmed the efficacy of our approach under static channel conditions. For example, measuring five frequency response samples over a bandwidth of 100 MHz and using a transmit power of 100 mW, valid users can be verified with 99% confidence while rejecting false users with greater than 95% confidence.

Although the content of sensor messages describing "events of interest" may be encrypted to provide confidentiality, the context surrounding these events may also be sensitive and therefore should be protected from eavesdroppers. An adversary armed with knowledge of the network deployment, routing algorithms, and the base-station (data sink) location can infer the temporal patterns of interesting events by merely monitoring the arrival of packets at the sink, thereby allowing the adversary to remotely track the spatio-temporal evolution of a sensed event. In this paper, we introduce the problem of temporal privacy for delay- tolerant sensor networks and propose adaptive buffering at intermediate nodes on the source-sink routing path to obfuscate temporal information from an adversary. We first present the effect of buffering on temporal privacy using an information-theoretic formulation and then examine the effect that delaying packets has on buffer occupancy. We evaluate our privacy enhancement strategies using simulations, where privacy is quantified in terms of the adversary's estimation error.

Accurately positioning nodes in wireless and sensor networks is important because the location of sensors is a critical input to many higher-level networking tasks. However, the localization infrastructure can be subjected to non-cryptographic attacks, such as signal attenuation and amplification, that cannot be addressed by traditional security services. We propose several attack detection schemes for wireless localization systems. We first formulate a theoretical foundation for the attack detection problem using statistical significance testing. Next, we define test metrics for two broad localization approaches: multilateration and signal strength. We then derived both mathematical models and analytic solutions for attack detection for any system that utilizes those approaches. We also studied additional test statistics that are specific to a diverse set of algorithms. Our trace-driven experimental results provide strong evidence of the effectiveness of our attack detection schemes with high detection rates and low false positive rates across both an 802.11 (WiFi) network as well as an 802.15.4 (ZigBee) network in two real office buildings. Surprisingly, we found that of the several methods we describe, all provide qualitatively similar detection rates which indicate that the different localization systems all contain similar attack detection capability.

Wireless sensor networks are susceptible to interference that can disrupt sensor communication. In order to cope with this disruption, we explore channel surfing, whereby the sensor nodes adapt their channel assignments to restore network connectivity in the presence of interference. We explore two different approaches to channel surfing: coordinated channel switching, where the entire sensor network adjusts its channel; and spectral multiplexing, where nodes in a jammed region switch channels while nodes on the boundary of a jammed region act as radio relays between different spectral zones. For spectral multiplexing, we have devised both synchronous and asynchronous strategies to facilitate the spectral scheduling needed to improve network fidelity when sensor nodes operate on multiple channels. In designing these algorithms, we have taken a system-oriented approach that has focused on exploring actual implementation issues under realistic network settings. We have implemented these proposed methods on a testbed of 30 Mica2 sensor nodes, and the experimental results show that these strategies can each repair network connectivity in the presence of interference without introducing significant overhead.

We investigate the achievable secrecy rate with Gaussian random codes when the main channel is an AWGN channel, while the eavesdropper's channel is Rayleigh fading with additive Gaussian noise. Several transmission strategies according to the main channel's relative channel gain are proposed and evaluated. We show that even if the main channel channel gain is arbitrarily worse than the eavesdropper's average channel gain, positive secrecy rate can still be achieved with artificial noise injection and a burst signaling strategy.

Many wireless networks are susceptible to spoofing attacks. Conventionally, ensuring the identity of the communicator and detecting an adversarial presence is performed via device authentication. Unfortunately, full-scale authentication is not always desirable as it requires key management and more extensive computations. In this paper, we propose noncryptographic mechanisms that are complementary to authentication and can detect device spoofing with little or no dependency on cryptographic keys. We introduce forge-resistant relationships associated with transmitted packets, and forge-resistant consistency checks, which allow other network entities to detect anomalous activity. We then provide several practical examples of forge-resistant relationships for detecting anomalous network activity. We explore the use of monotonic relationships in the sequence number fields, the use of a supplemental identifier field that evolves in time according to a reverse one-way function chain, and the use of traffic statistics to differentiate between anomalous traffic and congestion. We then show how these relationships can be used to construct classifiers that provide a multilevel threat assessment. We validate these methods through experiments conducted on the ORBIT wireless testbed.

Many wireless networks are susceptible to spoofing attacks, whereby an adversary imitates the network identifiers of legitimate devices. Conventionally, assuring the identity of the communicator and thereby detecting an adversarial presence is performed via device authentication. Unfortunately, full-scale authentication is not always desirable as it requires key management and more extensive computations. In this paper we argue that it is desirable to have a functionality complementary to traditional cryptographic authentication that can detect device spoofing with little or no dependency on cryptographic material. To accomplish this, we introduce the notion of forge-resistant relationships associated with transmitted packets, as well as forge-resistant consistency checks, which allow other network entities to detect anomalous activity. We then provide two practical examples of forge-resistant relationships for detecting anomalous network activity: we explore the use of a supplemental identifier field that evolves in time according to a reverse one-way function chain, and the use of signal strength readings for source discrimination. We validate the usefulness of these methods for anomalous "spoofed" traffic scenarios involving multiple sources sharing the same MAC address through experiments conducted on the ORBIT wireless testbed

We investigate the impact of landmark placement on localization performance using a combination of analytic and experimental analysis. For our analysis, we have derived an upper bound for the localization error of the linear least squares algorithm. This bound reflects the placement of landmarks as well as measurement errors at the landmarks. We next develop a novel algorithm, maxL minE, that using our analysis, finds a pattern for landmark placement that minimizes the maximum localization error. To show our results are applicable to a variety of localization algorithms, we then conducted a series of localization experiments using both an 802.11 (WiFi) network as well as an 802.15.4 (ZigBee) network in a real building environment. We use both received signal strength (RSS) and time-of-arrival (ToA) as ranging modalities. Our experimental results show that our landmark placement algorithm is generic because the resulting placements improve localization performance across a diverse set of algorithms, networks, and ranging modalities

Spoofing is a serious threat for both ad hoc and sensor networks, that can cause adverse effects on a network's operations. Although cryptographic authentication can assure the identity of a transmitter, authentication is not always desirable or possible as it requires key management and more extensive computations. In this paper we argue that it is desirable to have a functionality complementary to traditional authentication that can detect device spoofing with no dependency on cryptographic material. Towards this objective, we propose using forge-resistant relationships associated with transmitted packets to detect anomalous activity. Our strategy is generic, operates in a 1-hop neighborhood, and thus can locally provide protection in order to defend ad hoc or sensor networks from anomalous intrusions. As two specific constructions, we explore the use of monotonic relationships in the sequence number fields, and the enforcement of statistical characteristics of legitimate traffic. We then provide an example of how these relationships can be used to construct a classifier that provides a multi-level threat assessment. We validate the usefulness of these methods for anomalous traffic scenarios involving multiple sources sharing the same MAC address through experiments conducted on the ORBIT wireless testbed

Many techniques for multicast authentication employ the principle of delayed key disclosure. These methods introduce delay in authentication, employ receiver-side buffers, and are susceptible to denial-of-service (DoS) attacks. Delayed key disclosure schemes have a binary concept of authentication and do not incorporate any notion of partial trust. This paper introduces staggered timed efficient stream loss-tolerant authentication (TESLA), a method for achieving multigrade authentication in multicast scenarios that reduces the delay needed to filter forged multicast packets and, consequently, mitigates the effects of DoS attacks. Staggered TESLA involves modifications to the popular multicast authentication scheme, TESLA, by incorporating the notion of multilevel trust through the use of multiple, staggered authentication keys in creating message authentication codes (MACs) for a multicast packet. We provide guidelines for determining the appropriate buffer size, and show that the use of multiple MACs and, hence, multiple grades of authentication, allows the receiver to flush forged packets quicker than in conventional TESLA. As a result, staggered TESLA provides an advantage against DoS attacks compared to conventional TESLA. We then examine two new strategies for reducing the time needed for complete authentication. In the first strategy, the multicast source uses assurance of the trustworthiness of entities in a neighborhood of the source, in conjunction with the multigrade authentication provided by staggered TESLA. The second strategy achieves reduced delay by introducing additional key distributors in the network.

Many techniques for multicast authentication employ the principle of delayed key disclosure. These methods introduce delay in the verification of authentication, employ receiver-side buffers, and consequently are susceptible to denial of service (DoS) attacks. This paper introduces a method to reduce the delay needed to filter forged multicast packets, and consequently mitigates the effects of DoS attacks. Specifically, this paper introduces suitable modifications to the popular multicast authentication scheme, TESLA, through the use of multiple, staggered authentication keys that are used in creating message authentication codes (MACs) for a multicast packet. We provide guidelines for determining the appropriate buffer size, and show that the use of multiple MACs allows the receiver to flush potentially forged packets quicker than in conventional TESLA. As a result, staggered TESLA provides an advantage against DoS attacks as it requires an adversary to attempt a DoS at a higher attack rate than is necessary in conventional TESLA.

Digital fingerprinting protects multimedia content from being used for unauthorized purposes. One cost-effective strategy to attack digital fingerprints is collusion, where several colluders average their individual copies to disrupt the underlying fingerprints. In this work, we propose that fingerprints can be constructed using sequence sets satisfying the Welch bound equality (WBE). We further propose a detection algorithm utilizing sphere decoding that identifies the colluders from the colluded signal. We evaluate the performance of the proposed WBE-based anti-collusion codes (ACC) fingerprints with our proposed detection algorithm through simulations, and compare the performance of our scheme against orthogonal fingerprints and the BIBD anti-collusion codes proposed earlier. Simulation results show that the proposed WBE-based ACC and detection algorithm have better performance than BIBD-based ACC under the same configuration.

One of the most notable challenges threatening the successful deployment of sensor systems is privacy. Although many privacy-related issues can be addressed by security mechanisms, one sensor network privacy issue that cannot be adequately addressed by network security is source-location privacy. Adversaries may use RF localization techniques to perform hop-by-hop traceback to the source sensor’s location. This paper provides a formal model for the source-location privacy problem in sensor networks and examines the privacy characteristics of different sensor routing protocols. We examine two popular classes of routing protocols: the class of flooding protocols, and the class of routing protocols involving only a single path from the source to the sink. While investigating the privacy performance of routing protocols, we considered the tradeoffs between location-privacy and energy consumption. We found that most of the current protocols cannot provide efficient source-location privacy while maintaining desirable system performance. In order to provide efficient and private sensor communications, we devised new techniques to enhance source-location privacy that augment these routing protocols. One of our strategies, a technique we have called phantom routing, has proven flexible and capable of protecting the source’s location, while not incurring a noticeable increase in energy overhead. Further, we examined the effect of source mobility on location privacy. We showed that, even with the natural privacy amplification resulting from source mobility, our phantom routing techniques yield improved source-location privacy relative to other routing methods.

Many sensor applications are being developed that require the location of wireless devices, and localization schemes have been developed to meet this need. However, as location-based services become more prevalent, the localization infrastructure will become the target of malicious attacks. These attacks will not be conventional security threats, but rather threats that adversely affect the ability of localization schemes to provide trustworthy location information. This paper identifies a list of attacks that are unique to localization algorithms. Since these attacks are diverse in nature, and there may be many unforeseen attacks that can bypass traditional security countermeasures, it is desirable to alter the underlying localization algorithms to be robust to intentionally corrupted measurements. In this paper, we develop robust statistical methods to make localization attack-tolerant. We examine two broad classes of localization: triangulation and RF-based fingerprinting methods. For triangulation-based localization, we propose an adaptive least squares and least median squares position estimator that has the computational advantages of least squares in the absence of attacks and is capable of switching to a robust mode when being attacked. We introduce robustness to fingerprinting localization through the use of a median-based distance metric. Finally, we evaluate our robust localization schemes under different threat conditions.

The mobility provided by mobile ad hoc and sensor networks will facilitate new mobility-oriented services. Recent work has demonstrated that, for many issues, mobility is advantageous to network operations. This paper proposes that the need for mobility may be captured by formulating the movement of nodes as a classical dynamical system. Motivated by classical mechanics, we propose the notion of network dynamics, where the position and movement of mobile devices evolve according to forces arising from system potential functions that capture the operational goals of the network. We argue that, in the context of moving communicating nodes, the equations of motion should be formulated as a steepest descent minimization of the system potential energy. Further, since global information is not practical in sensor networks, we introduce distributed algorithms that yield more practical implementations of network dynamics. The resulting algorithms are generic, and may be applied to produce balanced network configurations for different initial network deployments. As a second application of network dynamics, we examine the problem of adapting a mobile sensor network to the threat of a jammer. We show that the combination of spatial escape strategies with network dynamics prevents network partitioning that might arise from a mobile jammer

Wireless networks are built upon a shared medium that makes it easy for adversaries to launch jamming-style attacks. These attacks can be easily accomplished by an adversary emitting radio frequency signals that do not follow an underlying MAC protocol. Jamming attacks can severely interfere with the normal operation of wireless networks and, consequently, mechanisms are needed that can cope with jamming attacks. In this paper, we examine radio interference attacks from both sides of the issue: first, we study the problem of conducting radio interference attacks on wireless networks, and second we examine the critical issue of diagnosing the presence of jamming attacks. Specifically, we propose four different jamming attack models that can be used by an adversary to disable the operation of a wireless network, and evaluate their effectiveness in terms of how each method affects the ability of a wireless node to send and receive packets. We then discuss different measurements that serve as the basis for detecting a jamming attack, and explore scenarios where each measurement by itself is not enough to reliably classify the presence of a jamming attack. In particular, we observe that signal strength and carrier sensing time are unable to conclusively detect the presence of a jammer. Further, we observe that although by using packet delivery ratio we may differentiate between congested and jammed scenarios, we are nonetheless unable to conclude whether poor link utility is due to jamming or the mobility of nodes. The fact that no single measurement is sufficient for reliably classifying the presence of a jammer is an important observation, and necessitates the development of enhanced detection schemes that can remove ambiguity when detecting a jammer. To address this need, we propose two enhanced detection protocols that employ consistency checking. The first scheme employs signal strength measurements as a reactive consistency check for poor packet delivery ratios, while the second scheme employs location information to serve as the consistency check. Throughout our discussions, we examine the feasibility and effectiveness of jamming attacks and detection schemes using the MICA2 Mote platform.

Digital fingerprinting is a method for protecting digital data in which fingerprints that are embedded in multimedia are capable of identifying unauthorized use of digital content. A powerful attack that can be employed to reduce this tracing capability is collusion, where several users combine their copies of the same content to attenuate/remove the original fingerprints. In this paper, we study the collusion resistance of a fingerprinting system employing Gaussian distributed fingerprints and orthogonal modulation. We introduce the maximum detector and the thresholding detector for colluder identification. We then analyze the collusion resistance of a system to the averaging collusion attack for the performance criteria represented by the probability of a false negative and the probability of a false positive. Lower and upper bounds for the maximum number of colluders K(max) are derived. We then show that the detectors are robust to different collusion attacks. We further study different sets of performance criteria, and our results indicate that attacks based on a few dozen independent copies can confound such a fingerprinting system. We also propose a likelihood-based approach to estimate the number of colluders. Finally, we demonstrate the performance for detecting colluders through experiments using real images.

The Diffie-Hellman problem is often the basis for establishing conference keys. In heterogeneous networks, many conferences have participants of varying resources, yet most conference keying schemes do not address this concern and place the same burden upon less powerful clients as more powerful ones. The establishment of conference keys should minimize the burden placed on resource-limited users while ensuring that the entire group can establish the key. In this paper, we present a hierarchical conference keying scheme that forms subgroup keys for successively larger subgroups en route to establishing the group key. A tree, called the conference tree, governs the order in which subgroup keys are formed. Key establishment schemes that consider users with varying costs or budgets are built by appropriately designing the conference tree. We then examine the scenario where users have both varying costs and budget constraints. A greedy algorithm is presented that achieves near-optimal performance, and requires significantly less computational effort than finding the optimal solution. We provide a comparison of the total cost of tree-based conference keying schemes against several existing schemes, and introduce a new performance criterion, the probability of establishing the session key (PESKY), to study the likelihood that a conference key can be established in the presence of budget constraints. Simulations show that the likelihood of forming a group key using a tree-based conference keying scheme is higher than the GDH schemes of Steiner et al.. Finally, we study the effect that greedy users have upon the Huffman-based conference keying scheme, and present a method to mitigate the detrimental effects of the greedy users upon the total cost.

The multimedia broadcast/multicast service (MBMS), which increases network efficiency, and facilitates group-oriented applications, is a service in 3G networks that is about to be standardized. A key security issue for MBMS is the design of a mechanism that controls access to multicast data. Traditionally, access control is done by distributing and maintaining key information. However, the existing architecture of mobile equipment prevents keys from being stored securely on the user side, making the traditional key management insufficient to protect the confidentiality of multicast data. Some discussion in 3GPP has addressed the issue, but the existing scheme achieves the security goal at the cost of high bandwidth overhead, unpredictable peak bandwidth and potential server implosion problems. Currently, no quantified convincing research has been done to study these issues. In this paper, we present new schemes that solve the problems, and quantify their scalability and bandwidth overhead.

Secure multicast applications require key management that provides access control. In wireless networks, where the error rate is high and the bandwidth is limited, the design of key management schemes should place emphasis on reducing the communication burden associated with key updating. A communication-efficient class of key management schemes is those that employ a tree hierarchy. However, these tree-based key management schemes do not exploit issues related to the delivery of keying information that provide opportunities to further reduce the communication burden of rekeying. In this paper, we propose a method for designing multicast key management trees that match the network topology. The proposed key management scheme localizes the transmission of keying information and significantly reduces the communication burden of rekeying. Further, in mobile wireless applications, the issue of user handoff between base stations may cause user relocation on the key management tree. We address the problem of user handoff by proposing an efficient handoff scheme for our topology-matching key management trees. The proposed scheme also addresses the heterogeneity of the network. For multicast applications containing several thousands of users, simulations indicate a 55%-80% reduction in the communication cost compared to key trees that are independent of the network topology. Analysis and simulations also show that the communication cost of the proposed topology-matching key management tree scales better than topology-independent trees as the size of multicast group grows.

In secure multicast applications, key management must be employed to provide access control to the multicast content In wireless networks, where the error rate is high and the bandwidth is limited, the design of key management schemes should place emphasis on reducing the communication burden associated with key updating and improving the reliability of key distribution. The topology-matching key management (TMKM) scheme has been proposed to reduce the communication burden associated with rekeying by matching the key tree to the network topology and localizing the transmission of rekeying messages. This scheme, however, is only suitable for homogeneous networks where mobiles users are uniformly distributed in the service area and experience similar delay and transmission error rates. In this paper, we present an improved topology-aware key management scheme that is suitable for a large-scale cellular wireless network where the heterogeneity of the network is taken into consideration. The proposed scheme not only reduces the communication overhead, but also improves the reliability of the key distribution.

Digital fingerprinting is a means to offer protection to digital data by which fingerprints embedded in the multimedia are capable of identifying unauthorized use of digital content. A powerful attack that can be employed to reduce this tracing capability is collusion. We study the collusion resistance of a fingerprinting system employing Gaussian distributed fingerprints and orthogonal modulation. We propose a likelihood-based approach to estimate the number of colluders, and introduce the thresholding detector for colluder identification. We first analyze the collusion resistance of a system to the average attack by considering the probability of a false negative and the probability of a false positive when identifying colluders. Lower and upper bounds for the maximum number of colluders are derived. We then show that the detectors are robust to different attacks. We further study different sets of performance criteria.

Digital fingerprinting of multimedia data involves embedding information in the content, and offers protection to the digital rights of the content by allowing illegitimate usage of the content to be identified by authorized parties. One potential threat to fingerprints is collusion, whereby a group of adversaries combine their individual copies in an attempt to remove the underlying fingerprints. Former studies indicate that collusion attacks based on a few dozen independent copies can confound a fingerprinting system that employs orthogonal modulation. However, since an adversary is more likely to collude with some users than other users, we propose a group-based fingerprinting scheme where users likely to collude with each other are assigned correlated fingerprints. We evaluate the performance of our group-based fingerprints by studying the collusion resistance of a fingerprinting system employing Gaussian distributed fingerprints. We compare the results to those of fingerprinting systems employing orthogonal modulation.

Digital fingerprinting is a means to offer protection to digital data by which fingerprints embedded in the multimedia are capable of identifying unauthorized use of digital content. A powerful attack that can be employed to reduce this tracing capability is collusion. In this paper, we study the collusion resistance of a fingerprinting system employing Gaussian distributed fingerprints and orthogonal modulation. We propose a likelihood-based approach to estimate the number of colluders, and introduce the thresholding detector for colluder identification. We first analyze the collusion resistance of a system to the average attack by considering the probability of a false negative and the probability of a false positive when identifying colluders. Lower and upper bounds for the maximum number of colluders K/sub max/ are derived. We then show that the detectors are robust to different attacks. We further study different sets of performance criteria.

The problem of controlling access to multimedia multicasts requires the distribution and maintenance of keying information. Typically, the problem of key management is considered separately from the problem of distributing the rekeying messages. Multimedia sources provide two approaches to distributing the rekeying messages associated with securing group communication. The first, and more conventional approach employs the use of a media-independent channel to convey rekeying messages. We propose, however, a second approach that involves the use of a media-dependent channel, and is achieved for multimedia by using data embedding techniques. Compared to a media-independent channel, the use of data embedding to convey rekeying messages provides enhanced security by masking the presence of rekeying operations. This covert communication makes it difficult for an adversary to gather information regarding the group membership and its dynamics. In addition to proposing a new mode of conveyance for the rekeying messages, we introduce a new message format that is suitable for multicast key management schemes. This new message format uses one-way functions to securely distribute new key material to subgroups of users. An advantage of this approach over the traditional message format is that no additional messages must be sent to flag the users which portion of the message is intended for them, thereby reducing communication overhead. We then show how to map the message to a tree structure in order to achieve desirable scalability in communication and computational overhead. Next, as an example of the interplay between the key management scheme and the mode of conveyance, we study the feasibility of embedding rekeying messages using a data embedding method that has been recently proposed for fractional-pel video coding standards such as H.263 and MPEG-2. Finally, since multimedia services will involve multiple layers or objects, we extend the tree-based key management schemes to include new operations needed to handle multilayer multimedia applications where group members may subscribe or cancel membership to some layers while maintaining membership to other layers.

Digital fingerprinting is an effective method to identify users who might try to redistribute multimedia content, such as images and video. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cheap and effective attack against such digital fingerprints is collusion, where several differently marked copies of the same content are averaged or combined to disrupt the underlying fingerprint. In this paper, we study the problem of designing fingerprints that can withstand collusion, yet trace colluders. Since, in antipodal CDMA-type watermarking, the correlation contributions only decrease where watermarks differ, by constructing binary code vectors where any subset of k or fewer of these vectors have unique overlap, we may identify groups of k or less colluders. Our construction of such anti-collusion codes (ACC) uses the theory of combinatorial designs, and for n users requires O(√n) bits. Further, we explore a block matrix structure for the ACC that reduces the computational complexity for identifying colluders and improves the detection capability when colluders belong to the same subgroup.

In the future, many multicast services will take place in the wireless domain. However, before these services can successfully be deployed, security infrastructures must be developed that manage the keys needed to provide access control to content. We present a method for designing multicast key management trees that are suitable for mobile wireless environments. By matching the key management tree to the cellular network topology, the total communication burden is reduced by 33%-45% compared to using the traditional key management trees that are independent of the topology.

Group-oriented services are attractive to both customers and service providers since they allow for potential markets that exploit user collaboration and shared experiences. In order to protect the content of a group service, the content must be encrypted using a key shared by group members. With the advancement of network technologies, customers will access group services from different networks using different terminals. The computational capabilities of the group members will vary. Contributory key agreement schemes have been developed to support secure communication between many senders and many receivers, but do not consider that users might require different amounts of time to perform a round of key establishment. In this paper, we develop a contributory key agreement scheme to setup the customer group which achieves a smaller latency for group key generation than existing schemes. We then address the latency needed to rekey the group during member joins and departures. A protocol that determines the location to place a joining member is presented that considers the time needed for rekeying the joining member as well as the effect the joining member has upon the departure times of the other group members. Simulations are presented that compare our algorithms with existing schemes for different group sizes, as well as different user join rates.

In order to secure communication amongst members of a conference, a secret shared by all group members must be established. The Diffie-Hellman problem is often the basis for generating keys in two-party communication, and can also be used to establish conference keys. In heterogeneous networks, many conferences have participants of varying computational power and resources. Most conference keying schemes do not address this concern and place the same burden upon less-powerful clients as more-powerful ones. The establishment of conference keys should try to minimize the burden placed on more resource-limited users while ensuring that the entire group can establish the group secret. In this paper, we present a scheme for establishing a conference key using the two-party Diffie-Hellman scheme. The scheme is hierarchical, forming subgroup keys for successively larger subgroups en route to establishing the group key. A full, binary tree called the conference tree governs the order in which subgroup keys are formed. Key establishment schemes that consider users with varying costs or budgets are designed by appropriately choosing the conference tree. The tree that minimizes the total group cost is produced via the Huffman algorithm. A criterion is presented for the existence of a conference tree when users have varying budgets, and a greedy algorithm is presented that minimizes the total length of the conference tree under budget constraints.

Digital fingerprinting is an effective method to identify users who might try to redistribute multimedia content, such as images and video. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cheap and effective attack against such digital fingerprints is collusion, where several differently marked copies of the same content are averaged or combined to disrupt the underlying fingerprint. We present a construction of collusion-resistant fingerprints based upon anti-collusion codes (ACC) and binary code modulation. ACC have the property that the composition of any subset of K or fewer codevectors is unique. Using this property, we build fingerprints that allow for the identification of groups of K or less colluders. We present a construction of binary-valued ACC under the logical AND operation using the theory of combinatorial designs. Our code construction requires only /spl Oscr/(/spl radic/n) orthogonal signals to accommodate n users. We demonstrate the performance of our ACC for fingerprinting multimedia by identifying colluders through experiments using real images.

The problem of controlling access to multimedia multicasts requires the distribution and maintenance of keying information. The conventional approach to distributing keys is to use a channel independent of the multimedia content. We propose a second approach that involves the use of a data-dependent channel, and can be achieved for multimedia by using data embedding techniques. Using data embedding to convey rekeying messages can provide an additional layer of security when compared with the traditional approach. We then introduce multicast key distribution, and employ a recent tree-based key distribution scheme to exhibit the factors involved in transmitting keys using data embedding.

The lifting scheme is used as a motivational tool for designing a better temporal subband scheme in video coding. The new subband coding scheme replaces the typical Haar filterbank. A simple criterion is used for the detection of scene changes in video sequences, and a modification to the Haar lifting scheme is developed that allows for adjusting the filterbank near a scene change. The new edge adaptive lifting scheme is applied to a scene change in video data and achieves improved performance at scene change frames when compared with the lifting Haar filterbank.