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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.

A dual purpose communication and radar system is considered, operating in the presence of a jammer. The system transmits communication signals and uses their reflections off targets to support target tracking. A game theoretic framework is used to design the system, i.e., determine power allocations, so that the performance of both communication and radar components is optimized. Two metrics are considered and compared for system design: (a) a weighted combination of signal-to-interference-plus-noise ratio (SINR) of the communication and radar components, reflecting the performance of both components; and (b) a weighted combination of the inverse SINRs of the corresponding components, reflecting the latency in the performance of the components. The comparison suggests that the latency metric enables a design that requires less a priori information on fading gains, and further, as the decision rule can be derived in closed form, the design is easier implementable in practice. The interaction between the system and the jammer is modeled by non-zero sum games. A Bayesian extension of the games allows us to investigate the impact that incomplete information about the underlying network parameters has upon the strategies that should be employed.

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.

In this paper, we study the problem of optimal power control for a single carrier communication system when it faces the combined threat of jamming and eavesdropping attacks. The ability for the jammer to react quickly to the user’s action is modeled by using the Stackelberg equilibrium with the jammer as the follower. Likewise, the case when the players have equal capabilities to react to each other is modeled by the players applying the Nash equilibrium strategy. It is shown that the jammer gains in the combined attack, when compared to an attack involving only jamming, since it can get larger payoff applying smaller power resource It is proven that although multiple equilibria could arise all of them return the same payoff to the user but different payoffs to the jammer. This phenomena could be utilized by the user to make the jammer to apply larger jamming resource consuming strategy and to increase SINR (signal-to-interference-plus-noise ratio) at the receiver without reducing corresponding secrecy utility.

The Spectrum Collaboration Challenge (SC2) was started by DARPA in 2016 to further expand the research on spectrum usage efficiency, and mitigate the ever-growing problem of spectrum scarcity. Teams that participated in SC2 designed and developed wireless networks, called Collaborative Intelligent Radio networks (CIRNs), to compete with other teams’ CIRNs. The scoring system was created to motivate maximizing both their own and other networks’ data throughput. To improve the spectrum usage efficiency, teams were encouraged to use Artificial Intelligence, as well as to collaborate with other teams and agree on spectrum usage schedules that work best for all parties. To facilitate this collaboration, DARPA has established the CIRN Interaction Language (CIL) – a language CIRNs can use to communicate with other networks and establish common spectrum goals and ways to achieve them. One of CIL’s main functionalities was to enable teams to announce their intended spectrum usage and provide information other teams can use to adapt their own channel selection. While potentially a beneficial concept, CIL’s effect on ensemble throughput of all networks was never evaluated, as a proper evaluation framework was never provided by DARPA, since it was not possible to disable it. This paper describes a simplified simulation of the spectrum usage announcement functionality of the CIL, explains the experiments run to evaluate CILs gains, and showcases the obtained results.

We consider a single carrier communication system subjected to jamming, and study optimal power control in the framework of game theory. The user’s transmission utility is the signal-to-interference plus noise ratio (SINR), and the user does not know with certainty whether the jammer is smart (i.e., it follows the best response strategy according to a Stackelberg game) or regular (i.e., it maximizes its payoff independent of the user, according to a Nash game). We formulate the problem as a Bayesian game, where the user knows only the probability of each jammer type (smart or regular), and find the equilibrium strategies in closed form. We show that the more probable a smart-type jammer is, the higher the payoffs of both players are. Considering the probability of each jammer type as a control parameter, and based on proportional fairness criteria, we find the optimal trade-off between smart-jamming and regular-jamming attacks.

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.

In this paper, we consider how subjectivity affects the problem of reliable communication. To model subjective factor we formulate a prospect theoretical (PT) extension of a zero sum game involving a primary user (PU) that must communicate with one of n users, while avoiding being jammed by an adversary. We prove that the PT equilibrium strategies, which are generalizations of the Nash equilibrium, exist for any probability weighting functions that models the corresponding subjective factors. Moreover, the PT-equilibrium strategy for the adversary is unique, and it can be found in water-filling form. We establish conditions for the PT-equilibrium of the PU to be unique. If PT-equilibrium of the PU is not unique, then a continuum of PT-equilibria arise. All of the PT-equilibria are found in water-filling form, and a hierarchical relationship between the derived water-filling equations is established. Finally, the sensitivity of the PT equilibrium strategies to environmental parameters is theoretically proven and numerically illustrated.

In this paper, we consider the problem of how a joint radar and communication system should divide its effort between supporting the radar and communication objectives when the system operates in an environment with hostile interference. In our model, we consider that the radar mode also represents a threat to the adversary since, while in this this mode, the adversary might be detected and eliminated. We model the problem by a stochastic game (SG) involving the joint radar/communication system and a jammer. To explore how irrational behavior by the rivals can affect the equilibrium strategies we formulate a Prospect Theory (PT) extension of the SG, which includes the solution of the original SG as boundary case. The stationary PT equilibrium strategies are found in closed form, and uniqueness of PT solution is proven.

This paper considers a joint radar and communication system that is attempting to support two different mission objectives: track a distant radar target and communicate with a distant communication receiver in the presence of a jammer. In such a scenario, the system can adjust its power allocation in the waveform design to support both objectives. Interference can undermine the operation of such a joint system and often the capabilities of the jammer are not known: the jammer might focus on disrupting one or both objectives. This uncertainty makes the design of an anti-jamming strategy difficult, and to devise an anti-jamming strategy we formulate the problem as Bayesian game between the system and the jammer, where the system knows only a priori probabilities for the jammer’s capabilities. The equilibrium strategies are found in closed form, and the impact of a priori probabilities regarding the jammer’s capability on the system anti-jamming strategy is illustrated.

The paper considers a dual purpose communication-radar system in the presence of a jammer. The system transmits communication signals and uses their reflections off targets for target tracking. The system uses transmission power P to maintain high throughput for its communication component and high signal-to-interference-plus-noise ratio (SINR) for its radar component, via maximization of a weighted combination of throughput and SINR. The jammer transmits a jamming signal of power J, targeting at reducing a weighted combination of the system throughput and SINR, where the weights are known to the system in statistical terms, via an a priori distribution of possible weights. The problem of selecting P and J is formulated as Bayesian game between the system and the jammer. The waterfilling equation for finding the equilibrium strategy is derived, and the equilibrium uniqueness is proved. The impact of a priori probabilities about jam-mer's preferences on the system anti-jamming strategy is illustrated.

In cognitive radio network, cognitive radios dynamically reconfigure themselves based on the spectrum opportunity. It is envisioned to be the key of overcoming the spectrum shortage. However, such reconfigurability also amplifies potential harmful interferences from non-compliant radios. In this paper, we propose ROSTER, a radio context attestation protocol for cognitive radio network. The proposed protocol is based on our observation that the compliance of a radio transmission depends on software configuration, radio configuration as well as the location and time of the device, which we call radio context. We believe radio context attestation, which allows the authority to verify the operational integrity of individual cognitive radio, is a fundamental security function for cognitive radio networks. To the best of our knowledge, we are the first to study this important problem. Different from conventional software attestation, ROSTER is designed to handle dynamic configurations in cognitive radios. Furthermore, special considerations are given in the protocol design to accommodate different levels of sensitivity in spectrum databases. Besides protocol design and security analysis, we also build a prototype of the proposed system using Raspberry Pi, USRP, and Amazon AWS. Network simulation using the benchmark measurements from the prototype shows the scalauility of our proposed protocol.

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 phase alignment among distributed transmitters, 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 × 3 m3 area. 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.

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 20×20×3m3 area. 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.

One of the challenges in jointly designing a system to support both communication and radar is that such a system has multiple objectives to address simultaneously. This challenge becomes more difficult when considering the potential for adversarial interference. A question that arises is what are appropriate design criteria that are stable when facing hostile interference, and from this arrive at realistic solutions to the trade-off between the two objectives. To address this question, we first show that the bargaining tradeoff can be correctly embedded in a uniform manner using the α-fairness tradeoff criteria. To investigate the impact of hostile interference, a zero sum game between the system and a jammer is formulated. It is proved that, within an interval for the fairness coefficient that is bounded by two cooperative solutions (maximizing total performance and minimizing total delay in objectives), the equilibrium exists and is unique. Moreover, the bargaining solution is the median point of this interval, while outside of this interval the existence of the equilibrium, and thus of stability of the system can be quite sensitive to jamming.

The connectivity of a communication link requires that the signal level be maintained at a threshold level above the noise floor. This is challenging when the link faces adversarial interference. In this paper, the problem of maintaining the link connectivity between a transmitter and receiver facing hostile interference is investigated using a game-theoretical formulation. The strategies for the rivals are the power levels employed by each, yielding a continuum of strategies for each player. Requiring that the signal to interference plus noise (SINR) level is higher than a threshold results in discontinuous player payoffs, and further results in the non-existence of a Nash equilibrium, thereby making the system unstable. However, observing the similarity between this game and the war of attrition game, we extend set of feasible strategies to mixed strategies that belong to the set of all measures over the continuum of feasible power levels. Using this observation, we prove that the equilibrium exists, is unique, and that the extension of the feasible strategies stabilizes the system.

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.

Wireless networks are vulnerable to many malicious attacks, like active interference, due to the shared and open-access nature of the wireless medium. One difficulty in dealing with interference attacks is the lack of knowledge about whether the attack will be present or not. In this paper, we investigate how the lack of knowledge of whether jamming will or will not be used against an OFDM communication impacts the anti-jamming strategy one should use. Our model can be applied more generally to jamming attacks with a fixed frequency where, at each time slot, it is unknown whether the interference will be used or not. We have derived the equilibrium strategy in waterfilling form, and shown that the obtained solution includes as boundary cases two classical solutions in OFDM transmission for the case where there is no adversary, and the case where the adversary attacks with certainty. Uniqueness of the equilibrium strategies is proven, and an algorithm for finding the parameters of the waterfilling equations is developed. The efficiency of the algorithm is illustrated by numerical examples.

Practical generation of secret bits using wireless channel measurements between two terminals is presented in this paper. The model used for this implementation assumes imperfect reciprocity between the channel measurements made by the two terminals in the presence of a passive eavesdropper. The channel measurements (e.g., received signal strength values) are used to estimate the secret key rate in order to establish the number of secret bits that can be generated between any two terminals. The main contributions of this paper are: 1) algorithm to generate uncorrelated channel measurements even when channel measurement statistics between the two terminals are time-varying; 2) development of a reconciliation algorithm based on BCH codes, where the statistics of error between bits generated by the two terminals is not known a priori; and 3) implementation of secret bit generation using channel reciprocity in a Linux environment. The channel measurement data that was collected for this paper is available at http://downloads.i-a-i.com/RAPOR.

Maintaining both reliable and secret communication involves different objectives: ensuring sufficient throughput for reliable communication and ensuring the secrecy of the associated communication. The optimal solution for one of these objectives might not be optimal or even suitable for another objective and thus a question arises as to what is the appropriate criteria for fairly balancing these objectives. We solve this problem in two steps. In the first step,we use the α-fairness criteria for formulating the tradeoff between these objectives. Its advantage is that it allows one to consider a continuum of fairness criteria in a unified framework, from cooperative fulfilment of both objectives (for α = 0) to a maxmin scenario as α tends to infinity. In the second step, by means of bargaining over the continuum of obtained optimal fair solutions, we find the solution that is optimally fair. We illustrate the suggested approach by a closed-form solution obtained for transmission in the low SNR regime.

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.

Security is a fundamental problem facing wireless systems employing spectrum sharing, and thus scanning algorithms are used to detect malicious or illegal activity in such systems. A crucial issue in designing such algorithms is incorporating knowledge about the environment, as well as what knowledge an adversary might have, into the scanning algorithm to improve detection performance. In particular, if such knowledge is initially incomplete, it becomes desirable to adapt one's knowledge based upon the results of the scanning activities, so as to further improve detection performance. To obtain insight into this problem, we suggest a Bayesian game-theoretical model of bandwidth scanning with learning. We show that such knowledge could change the structure of the strategies employed from distributing effort among all the bands, to band-sharing or even band on/off strategies and improve detection performance. Also, we have shown that a lack of information for the scanner compare to the adversary makes the scanner strategy more sensitive to the information he has.

This paper investigates the co-existence of Wi-Fi and LTE in emerging unlicensed frequency bands which are intended to accommodate multiple radio access technologies. Wi-Fi and LTE are the two most prominent access technologies being deployed today, motivating further study of the inter-system interference arising in such shared spectrum scenarios as well as possible techniques for enabling improved co-existence. An analytical model for evaluating the baseline performance of co-existing Wi-Fi and LTE is developed and used to obtain baseline performance measures. The results show that both Wi-Fi and LTE networks cause significant interference to each other and that the degradation is dependent on a number of factors such as power levels and physical topology. The model-based results are partially validated via experimental evaluations using USRP based SDR platforms on the ORBIT testbed. Further, inter-network coordination with logically centralized radio resource management across Wi-Fi and LTE systems is proposed as a possible solution for improved co-existence. Numerical results are presented showing significant gains in both Wi-Fi and LTE performance with the proposed inter-network coordination approach., Comment: Accepted paper at IEEE DySPAN 2015

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.

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.

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. I. INTRODUCTION

In emulating a multi-node wireless network, received interference can be represented by combining the multipath responses of the interfering links. Each multipath response can be described by a set of mean-squared amplitude of the multipath components and relative delays. The number of filter taps required per link to emulate the actual (‘true’) channel is a function of the channel bandwidth W and RMS delay spread τ rms . Assuming each per-link channel to have an exponentially decaying power delay profile, this value is about 4Wτ rms . We propose to emulate each link using n uniformly-spaced taps of equal mean-square gain. For this case, the required number of taps is only 2Wτ rms , while maintaining the important characteristic (i.e., the CDF of total power, taken over the fading) of the true channel. We derive this result analytically and confirm it by simulation. Improving on this 50% reduction in required taps, we further show that the loss in accuracy is significantly low so long as the total number of taps is the order of 16 or more. For large values of Wτ rms , this can lead to even more reduction in n and, thus, further limit the cost and complexity of emulators.

Transferring the role of leadership between members of a team is an important requirement in tactical operations as it allows an operation to continue in spite of unforeseen events. Delegation, at first glance, appears to be the simple act of giving someone else a right that one possesses. However, this basic function is challenging to implement electronically, and thus there is a need for mechanisms to enforce flexible delegation policies in distributed systems. It has been shown that Law Governed Interaction (LGI) can address these challenges based on the assumption of the trustworthiness of its own enforcement infrastructure. However, to meet the needs of tactical missions, the proposed mechanism should also be resilient to the Byzantine compromise of the infrastructure. Therefore, in this paper we extend the original LGI model to provide containment, guaranteeing that a single Byzantine agent cannot compromise the properties of the system and in general, our approach can withstand the presence of multiple Byzantine agents as long as a correlated pair of agents is not corrupt.

Many modern communications systems use Orthogonal Frequency Division Modulation (OFDM). These systems need to synchronize the receiver and equalize the channel to achieve good performance. The algorithms used to perform timing synchronization and channel estimation/equalization typically are designed without considering whether an adversarial signal could disrupt these subsystems. In typical scenarios, a jammer would not have reliable (or any) knowledge of the channels filtering the target or jamming signals. Thus, in this paper, we consider attack strategies that do not require channel knowledge. We study the efficiency of several jamming strategies targeting each subsystem as measured by the peak and average signal-to-jamming ratio (SJR) required to achieve signal denial for each method and find that jamming the timing can be substantially more efficient than other jamming strategies. We also discuss modifications to the jamming strategies that might be necessary for real-world operation.

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., for values 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.

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

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.