The growth of Smartphones has bridged the telephony/SMS and the IP worlds, and this has resulted in new opportunities for financially motivated attackers. For example, some malicious campaigns in the cellular network aimed at extracting money fraudulently can do so even without any malware. Detecting and mitigating the variety of attacks in cellular network is difficult because they do not necessarily have a fixed 'signature', and new types of campaigns appear frequently. Further complicating matters, detecting a single malicious entity (a domain name, a phone number, or a short code) that is part of a malicious campaign, is usually not very effective, because the attacker simply moves to using another entity in its place. An effective strategy requires detecting all/most elements involved in the campaign at once. In this paper, we describe a system, based on ideas from anomaly detection and clustering, that aims to detect many different families of widespread malicious campaigns in cellular networks. The system reveals an entire campaign as a graph cluster which includes the various entities involved in the campaign and their relationship, such as malware download websites, C&C servers, spammers, etc. Using logs from both SMS and IP portions of the network for millions of users, we detect newly popular entities and cluster them to discover how they are related. By looking for cues of possible malicious behavior from any of the entities in a cluster, we attempt to ascertain whether a detected campaign might be malicious, providing valuable leads to a human analyst. Our system is live and generates daily clusters for human analysts. We provide detailed case studies of real, previously unseen families of malicious campaigns that this system has successfully brought to light.

If an outbound flow is observed at the boundary of a protected network, destined to an IP address within a few addresses of a known malicious IP address, should it be considered a suspicious flow? Conventional blacklisting is not going to cut it in this situation, and the established fact that malicious IP addresses tend to be highly clustered in certain portions of IP address space, should indeed raise suspicions. We present a new approach for perimeter defense that addresses this concern. At the heart of our approach, we attempt to infer internal, hidden boundaries in IP address space, that lie within publicly known boundaries of registered IP netblocks. Our hypothesis is that given a known bad IP address, other IP address in the same internal contiguous block are likely to share similar security properties, and may therefore be vulnerable to being similarly hacked and used by attackers in the future. In this paper, we describe how we infer hidden internal boundaries in IPv4 netblocks, and what effect this has on being able to predict malicious IP addresses.

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.

The increasing density and data rate of unlicensed band wireless devices in small office and home (SOHO) environments has led to significant inter- and intra-radio interference problems. Multiple competing standards such as the IEEE 802.11b/g, Bluetooth and ZigBee, all of which operate in the 2.4 GHz ISM band, can interfere with each other when used in typical indoor environments, potentially causing significant performance degradation. This paper presents detailed experimental results (using the ORBIT radio grid testbed) to quantify the effects of such interference in representative SOHO scenarios. In particular, different topologies, traffic loads and number of interfering devices are emulated to show the impact of multi-radio interference and to characterize each kind of interference. Further, a cross-layer, multi-radio interference diagnosis framework (called “spectrum MRI”) is described with the aim of isolating and classifying multi-radio interference problems using heuristic and model-based methods. A specific example of identifying interference problems which may affect an 802.11g video link is given to illustrate the proposed measurement and diagnosis framework.

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.

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.

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.

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.

Cooperation between rational users in wireless networks is studied using coalitional game theory. Using the rate achieved by a user as its utility, it is shown that the stable coalition structure, i.e., set of coalitions from which users have no incentives to defect, depends on the manner in which the rate gains are apportioned among the cooperating users. Specifically, the stability of the grand coalition (GC), i.e., the coalition of all users, is studied. Transmitter and receiver cooperation in an interference channel (IC) are studied as illustrative cooperative models to determine the stable coalitions for both flexible (transferable) and fixed (non-transferable) apportioning schemes. It is shown that the stable sum-rate optimal coalition when only receivers cooperate by jointly decoding (transferable) is the GC. The stability of the GC depends on the detector when receivers cooperate using linear multiuser detectors (non-transferable). Transmitter cooperation is studied assuming that all receivers cooperate perfectly and that users outside a coalition act as jammers. The stability of the GC is studied for both the case of perfectly cooperating transmitters (transferrable) and under a partial decode-and-forward strategy (non-transferable). In both cases, the stability is shown to depend on the channel gains and the transmitter jamming strengths.

The formation of coalitions in a Gaussian interference channel where the receivers are allowed to cooperate is studied under the framework of coalitional game theory. Allowing any arbitrary sharing of the total rate achieved by a coalition between its member links, it is shown that the grand coalition (coalition of all links) maximizes spectrum utilization and is also stable, that is, the links in this coalition have no incentives to leave and form other coalitions. The issue of fairness in allocating rates to members of a grand coalition is addressed via a Nash bargaining solution where each link utility is modeled as the rate gained by being in a coalition relative to the rate achieved in the interference channel. Further, a rate allocation solution using proportional fairness is also presented and the results are illustrated with examples