This paper introduces DISPERSE, a distributed scalable architecture for delivery of content and services that provides resilience against node failure through location-independent storage and replication of content. Current content delivery networks (CDNs) have, at least to some degree, a centralized structure thus susceptible to a single point of failure. DISPERSE addresses this limitation by implementing a fully de-centralized structure. DISPERSE is a two-layer architecture: the first layer (front-end layer) exposes services (e.g., Web, SFTP) to clients; the second layer (back-end layer) provides reliable distributed storage of content and application state. Content in DISPERSE's back-end layer is stored and exchanged as Named Data Network (NDN) content objects. This allows DISPERSE to implement fine-grained, location-independent, fully decentralized content replication mechanisms. We validate the performance of DISPERSE under two node failure scenarios. In the first scenario, content can be stored in any DISPERSE node, and all nodes are equally likely to fail. In this scenario, we use non-linear optimization techniques to determine the optimal number of content copies under availability and latency constraints. In the second scenario, different nodes fail with different probabilities, and content is stored in nodes according to its value, node failure probability, and resource availability. This scenario is addressed as an instance of the minimum cost flow problem. Our results show that DISPERSE reduces the failure of content retrieval by five orders of magnitude compared to common CDN implementations, without significantly increasing content retrieval delay. Further, numerical results show that DISPERSE improves content availability by a factor of 1.3× - 2.3× when deploying the minimum cost flow algorithm.

Internet users can be classified as two types: (a) active users-actively contribute to blogs, publish opinions, write comments in Youtube, tweet messages, etc. and (b) passive consumers who only consume Internet information without contributing to it. While the majority of current social media research deals with active user analysis, there is very little work in understanding the dynamics of passive consumers and their influence. Our global scale Internet measurement of user access patterns of a diverse set of Internet media services indicates conclusively that majority of consumers are passive. In this paper, we develop a spatio-temporal mathematical model and the corresponding stochastic analysis to understand the passive consumer dynamics. Both discrete and continuous time analysis are presented. We also show how the analysis can be used to identify spatial points of influence, i.e., spatial locations that have maximum expertise or influence on a topic. The analysis takes into account, the initial level of consumption at each spatial location and the influence of different passive consumers at different geographic locations on each other. The effect of information noise is taken into account to derive fundamental limits of passive information consumption. Theoretical results are verified using real Internet measurement data. The large scale data have been made available for other researchers.

Information consumers in online social networks receive information from multiple information providers, which results in confusion. The amount of confusion depends on three main factors-(a) attributes of the source, (b) characteristics of the consumer and (c) trust relation between the information provider and the consumer. While information confusion has been qualitatively observed in social networks, no quantitative model or analysis was presented. We present the first quantitative model to analyze confusion in the presence of multiple information providers. We address the following fundamental issues-(i) What is a good model for confusion? (ii) How does the quality of information degrade due to confusion? (iii) What are good strategies for the information providers to control the power or the intensity with which the information is transmitted? The scenario is modeled as a non-cooperative game with pricing, whose Nash equilibrium provides the solution to the questions posed above. We use data from Twitter (e.g., on full body scan in airports) and diabetes outreach networks to illustrate the analysis. We use the solution of the non-cooperative game to study the confusion levels of consumers, in terms of the aggressiveness and passiveness of the information providers. Results indicate that confusion levels are high in in networks in which all information providers are equally trusted. In networks where information providers are unequally trusted, the confusion levels are moderate.

The authors present a distributed channel acquisition mechanism in dynamic spectrum access (DSA) networks. A novel graph MAximum SPECTrum packing algorithm (MASPECT) is proposed for a system with N secondary networks. Each secondary network makes use only of the local topology information to resolve contentions during channel access. The proposed algorithm also adapts easily to topological changes. Most approaches to channel acquisition use either centralised graph colouring or distributed approaches that result in under utilisation of spectrum. The authors show that the proposed MASPECT algorithm results in improvements by up to one order of magnitude in the spectrum utilisation for the secondary networks and results in Jain's fairness index of about 0.9. The authors further present a modified probabilistic heuristic, PMASPECT, that improves the termination time of the algorithm by up to two orders of magnitude. The authors also study the impact of the MASPECT algorithm on each individual secondary networks in the system in the presence of primary activity. For each secondary network, the proposed algorithm results in up to two orders of magnitude of reduction in the call blocking dropping probabilities in the presence of primary activity.

We present a game theoretic power control of overlay/overt communications to maximize the goodput (effective throughput of error-free bits) of multi-terminal covert timing channels. Most approaches in the literature on covert timing channels discuss capacities of the timing channels but do not study how the overlay communication can be controlled to maximize the goodput of covert timing channels. We study the factors of the overlay communication that affect the goodput of each timing channel in a multi-terminal covert timing network. We show that the goodput of the covert timing channel can be enhanced by increasing the rate of overlay transmission and by game theoretic power control of overlay communication. We finally extend the game theoretic power control to maximize the goodput of each covert timing channel in a multi-terminal covert timing network by maximizing the asymptotic spectral efficiency of the overlay communication.

Primary user emulation attack (PUEA) is a denial of service (DoS) attack unique to dynamic spectrum access (DSA) networks. While there have been studies in the literature to detect and mitigate PUEA, the impact of PUEA on the performance of secondary networks has seldom been studied. In this paper, we analyze how PUEA affects call dropping and delay in secondary networks carrying both real-time traffic and non-real-time traffic. Numerical results indicate that PUEA can increase the number of dropped calls by up to two orders of magnitude and can increase the mean delay by up to a factor larger than two. We then evaluate the performance of secondary networks that deploy the protocols which we proposed previously to mitigate PUEA. Our protocols reduce the number of dropped calls by up to one order of magnitude. Our protocols are also shown to exhibit almost the same delay performance as that of a system with no PUEA, for low malicious traffic load. When malicious traffic load is high, our protocols provide an improvement on the delay performance by up to 54%.

We address a unique security vulnerability in long term evolution (LTE) advanced and high speed packet access (HSPA+) wireless networks due to carrier/channel bonding. This vulnerability is shown to result in various amounts of service disruption based on the radio network parameters and the user locations. Typically, channel bonding have been perceived as a means to enhance the bandwidth and throughput for the users. However, this could also result in the loss of orthogonality between the bonded spectrum bands. We show that this leads to a security vulnerability that can be exploited by an attacker to cause service disruption. In this case, the attacker need not even operate in the same bands as the user, to be effective. We present an analysis to compare the loss in throughput caused by the vulnerability due to channel bonding in advanced LTE and HSPA+ networks. Results indicate that channel bonding is susceptible to about 70% loss of throughput in LTE networks and about 11-15% in HSPA+ networks compared to systems with no bonding. Also, users farther away from the base station suffer larger throughput degradation due to channel bonding in LTE networks, while it causes larger degradation in throughput for near users in HSPA+ networks. To the best of our knowledge, this is the first attempt to identify and analyze a significant security vulnerability in LTE and HSPA+ networks.

We address a unique security threat that arises due to channel fragmentation (or aggregation or bonding) in dynamic spectrum access (DSA) based IEEE 802.22 networks. Typically, channel fragmentation, aggregation and bonding have been studied in the literature as a means to enhance the spectrum utilization. However, the loss of orthogonality between the spectrum bands due to channel fragmentation, aggregation or bonding can be exploited by malicious attackers to cause a cognitive service disruption. We present an analysis of such a threat. We determine the optimal transmit powers a malicious attacker transmits on each fragment, so as to create maximum service disruption. Numerical results indicate that a malicious attacker can cause up to about 16% loss in the capacity of the system as a consequence of fragmentation. Detailed analysis is presented for channel fragmentation and can be easily applied to channel aggregation and bonding. To the best of our knowledge,this is the first analysis of such cognitive service disruption threats due to fragmentation.

We study the dynamics of social networks in terms of population growth and control of user behavior. Most of the current research in social networks focus on static analysis through graph theoretic models to represent the networks or focus on modeling the traffic. Here, we study the cost of collaborative vs individualistic behavior of users in order to grow their network size in a social network. Each user incurs a cost (monetary or emotional) for collaboration. We formulate the behavior of the users as a non-linear optimization problem with a cost. The objective function of the optimization problem is obtained using a stochastic analysis of population growth in social networks, based on the first-passage time of a birth-death process. The stochastic model is validated by comparison with real data obtained from Twitter Results indicate that a homogeneous social network (in which users have similar characteristics) will be individualistic. However, heterogeneous social networks (users with different characteristics) exhibit a threshold effect, i.e., there is a minimum cost, below which the network is as collaborative as desired and a maximum cost above which the network is individualistic as required. To the best of our knowledge, this is one of the first analysis of dynamics of user behavior and temporal population growth in social networks.

We propose a spectrum decision protocol resilient to primary user emulation attacks (PUEA) in dynamic spectrum access networks. PUEA is a type of denial-of-service attack that can severely interfere with the spectrum sensing process and unfairly deprive legitimate secondary users of spectrum access. In this paper, we present a robust spectrum decision protocol that can mitigate PUEA using individual spectrum decisions made by secondary nodes in the network. In order to enable each secondary node to make an individual spectrum decision to detect PUEA, we first characterize the received power at good secondary user. This is done by using a flexible log-normal sum approximation. The received power thus characterized is used to determine the probability of successful PUEA on each secondary user, which is used to develop the proposed protocol. Simulation results demonstrate that the proposed protocol can significantly reduce the probability of successful PUEA under Byzantine attacks (i.e., when the malicious users intentionally provide false spectrum decisions), while still following the spectrum evacuation etiquette.

Primary user emulation attack (PUEA) is a denial of service (DoS) attack unique to dynamic spectrum access (DSA) networks. While there have been studies in the literature to detect and mitigate PUEA, the impact of PUEA on the call blocking and call dropping probabilities of users in secondary networks has not been studied. We present the first analysis to study the impact of PUEA on the secondary users in terms of call blocking and call dropping. We propose a three dimensional continuous time Markov chain (3D-CTMC) to model the channel occupancy in DSA networks. We use the 3D-CTMC to determine the call blocking and call dropping probabilities for secondary users. We validate our analysis with simulations. Results indicate that while PUEA does not affect the call blocking probability, it can increase the call dropping probability of secondary users by more than one order of magnitude. We also evaluate the call dropping performance of some of our previously proposed protocols to mitigate PUEA. We show that our protocols can improve the call dropping performance by about 40% for high traffic loads of malicious users and can provide almost the same performance as that of a system with no PUEA, when the malicious user traffic is low.

We discuss malicious interference based denial of service (DoS) attacks in multi-band covert timing networks using an adversarial game theoretic approach. A covert timing network operating on a set of multiple spectrum bands is considered. Each band has an associated utility which represents the critical nature of the covert data transmitted in the band. A malicious attacker wishes to cause a DoS attack by sensing and creating malicious interference on some or all of the bands. The covert timing network deploys camouflaging resources to appropriately defend the spectrum bands. A two tier game theoretic approach is proposed to model this scenario. The first tier of the game is the sensing game in which, the covert timing network determines the amount of camouflaging resources to be deployed in each band and the malicious attacker determines the optimal sensing resources to be deployed in each band. In the second tier of the game, the malicious attacker determines the optimal transmit powers on each spectral band it chooses to attack. We prove the existence of Nash equilibriums for the games. We compare the performance of our proposed game theoretic mechanism with that of other well known heuristic mechanisms and demonstrate the effectiveness of the proposed approach.

We study the optimum location of an eavesdropper from a secrecy capacity perspective in multiterminal networks with power control. We determine the logical location of an eavesdropper (represented by the channel gain from all the transmitters) which 1) results in zero secrecy capacity for maximum number of users in the network and 2) results in zero secrecy capacity for the bottle-neck links. We then analyze the asymptotic secrecy capacity of the system and the asymptotic behavior of the optimum logical location of the eavesdropper. Results indicate that power control can make eavesdropping more difficult as it results in infeasible locations for the eavesdropper. Power control is also shown to provide scenarios which can result in positive asymptotic secrecy capacity for all the users.

In this paper, we present an analytical model as well as a practical mechanism to detect denial of service (DoS) attacks on secondary users in dynamic spectrum access (DSA) networks. In particular, we analyze primary user emulation attacks (PUEA) in cognitive radio networks without using any location information and therefore can do away with dedicated sensor networks. We present an analysis using Fenton's approximation and Wald's sequential probability ratio test (WSPRT) to detect PUEA. Simulation results demonstrate that it is possible to keep the probability of success of PUEA low, while still keeping the probability of missing the return of the primary low as well.