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We consider the communication between a source (user) and a receiver in the presence of multiple jammers, and study resource assignment in a non-cooperative game theory framework using communication latency as the user's utility. Equilibrium strategies are found in closed form, and their uniqueness is proven. This allows one to identify jammers whose equilibrium strategies have an on/off structure, or they are sensitive to small variations in the network parameters.

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.

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.

Wireless power transfer (WPT) promises to deliver energy to devices that are otherwise hard to charge or replace batteries for. This paper presents a new power transfer approach by aligning the phases of a collection of radio frequency (RF) energy chargers at the target receiver device. Our approach can ship energy over tens of meters and to mobile targets. More importantly, our approach leads to a highly asymmetric energy density distribution in the charging area: the energy density at the target receiver is much higher than the energy density at other locations. It is a departure from existing beamforming based WPT systems that have high energy along the energy beam path. Such a technology can enable a large array of batteryless Internet of Things applications and render them much more robust and long-running. Thanks to its asymmetric energy distribution, our approach potentially can be scaled up to ship higher level of energy over longer distances. In this paper, we design, prototype, and evaluate the proposed energy transfer approach, referred to as Energy-Ball. We implement an Energy-Ball testbed that consists of 17 N210 and 4 B210 Universal Software Radio Peripheral (USRP) nodes, yielding a 20 x 20 m2 energy delivery area. We conduct carefully designed experiments on the testbed. We demo that the energy density of Energy-Ball at the target spot is considerably higher than the energy density elsewhere, with the peak to average power ratio of 8.72. We show that Energy-Ball can transfer energy to any point within the area. When the receiver moves at a speed of 0.5 m/s, Energy-Ball can transfer 80% of optimal power to the mobile receiver. Further, our results also show Energy-Ball can deliver over 0.6mw RF power that enables batteryless sensors at any point across the area.

In medical treatments, a fundamental dilemma often arises: on the one hand, an increase in a drug's dose could lead to a stronger, therapeutic treatment response, but on the other hand this could also lead to increased toxicity risks. In this paper, we propose to solve this dilemma using a Nash bargaining approach. To do so, we reformulate the tradeoff problem in an equivalent form as a dilemma between a drug's beneficial response and the drug's safety, where the dilemma then becomes a two-objective problem with safety and response as the objectives. Using a general receptor response model, we show that the set of all feasible outcomes associated with a drug's treatment is characterized as a convex set, which allows the dilemma to be solved as a bargaining problem between the two objectives. The Nash bargaining solution (NBS) is found in closed form, and interesting properties associated with the solution are presented. In particular, it is shown that one can interpret the NBS as corresponding to a treatment giving the maximal expected safe treatment response associated with the drug. Moreover, the condition when the NBS coincides with the maxmin solution for the two objectives is derived. Two approaches to control the NBS solution are then presented: first, by means of assigning bargaining powers to objectives; second, by means of assigning an upper-bound on the drug's dosage. The obtained NBS are compared with the dosage returning maximal drug response efficiency.

In this work, we propose a system that detects approaching cars for smartphone users. In addition to detecting the presence of a vehicle, it can also estimate the vehicle’s driving direction, as well as count the number of cars around the user. We achieve these goals by processing the acoustic signal captured by microphones embedded in the user’s mobile phone. The largest challenge we faced involved addressing the fact that vehicular noise is predominantly due to tire-road friction, and therefore lacked strong (frequency) formant or temporal structure. Additionally, outdoor environments have complex acoustic noise characteristics, which are made worse when the signal is captured by non-professional grade microphones embedded in smartphones. We address these challenges by monitoring a new feature: maximal frequency component that crosses a threshold. We extract this feature with a blurred edge detector. Through detailed experiments, we found our system to be robust across different vehicles and environmental conditions, and thereby support unsupervised car detection and counting. We evaluated our system using audio tracks recorded from seven different models of cars, including SUVs, medium-sized sedans, compact cars, and electric cars. We also tested our system with the user walking in various outdoor environments including parking lots, campus roads, residential areas, and shopping centers. Our results show that we can accurately and robustly detect cars with low CPU and memory requirements.

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.

Journal of Cybersecurity and Privacy is critical to society at large, and its importance is growing daily. The rapid advancement in technology has caused a large-scale integration of computing, communication, and information technologies into virtually every aspect of our modern society[...]

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.

Underlay is an aggressive spectrum sharing paradigm that allows secondary nodes to be active simultaneously with the primary nodes through interference cancelation (IC). In this paper, we design an online admission control algorithm to handle dynamic session arrival and departure in the underlay coexistence paradigm for multi-hop primary and secondary networks. For IC, we employ multiple antennas at each secondary node. Through distributed computation and degree-of-freedom (DoF) allocation at each secondary node, our algorithm ensures that all interference to/from the multi-hop primary network and interference within the multi-hop secondary network are canceled properly so that data transport is free of interference in both multi-hop primary and secondary networks. Further, we show that the DoF allocation by our algorithm is feasible (implementable) at the physical layer at all time. Through extensive performance evaluation, we find that our online admission control algorithm can offer competitive performance when compared to an offline centralized algorithm.

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.

Spectrum sharing enables radar and communication systems to share the spectrum efficiently by minimizing mutual interference. Recently proposed multiple-input multiple-output radars based on sparse sensing and matrix completion (MIMO-MC), in addition to reducing communication bandwidth and power as compared with MIMO radars, offer a significant advantage for spectrum sharing. The advantage stems from the way the sampling scheme at the radar receivers modulates the interference channel from the communication system transmitters, rendering it symbol dependent and reducing its row space. This makes it easier for the communication system to design its waveforms in an adaptive fashion so that it minimizes the interference to the radar subject to meeting rate and power constraints. Two methods are proposed. First, based on the knowledge of the radar sampling scheme, the communication system transmit covariance matrix is designed to minimize the effective interference power (EIP) at the radar receiver, while maintaining certain average capacity and transmit power for the communication system. Second, a joint design of the communication transmit covariance matrix and the MIMO-MC radar sampling scheme is proposed, which achieves even further EIP reduction.

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.

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.

In this paper, we suggest a new class of anti-jamming problems where the type of intelligence associated with a jamming attack is unknown. Specifically, we consider a problem where the nodes of a peer-to-peer network do not know whether the network is under attack by a random jammer (which might be considered as a natural background noise), or an intelligent one (i.e., the jammer who can adapt his strategy based on knowledge gained during attacks). The goal of the nodes is to identify the type of the attack based on knowledge obtained from the attack in previous time slots, and thereby to reduce the efficiency of the jamming attack. First, we model the problem as a Bayesian game for a single time slot attack, and reduce it to the solution of dual linear programming (LP) problems. Additionally, the convergence of the fictitious play algorithm for finding the equilibrium is established. Then, we develop the problem for a repeated jamming attack, where the nodes adapt their beliefs based on history of the previous attacks. In particular, we have shown that it is possible for the nodes in the network to always be able to identify the jammer’s type within a finite number of time slots.

Part 2: Security and Network Management; International audience; The success of a UAV mission depends on communication between a GCS (Ground Control Station) and a group of UAVs. It is essential that the freshness of the commands received by UAVs is maintained as mission parameters often change during an operation. Ensuring the freshness of the commands received by UAVs becomes more challenging when operating in an adversarial environment, where the communication can be impacted by interference. We model this problem as a game between a transmitter (GCS) equipped with directed antennas, whose task is to control a group of UAVs to perform a mission in a protected zone, and an interferer which is a source spherically propagated jamming signal. A fixed point algorithm to find the equilibrium is derived, and closed form solutions are obtained for boundary cases of the resource parameters.

In this paper we consider the problem of maintaining communication between a transmitter and a receiver in the presence of hostile interference. To maintain communication the transmitter must keep the SINR greater or equal to an SINR threshold, while the adversary aims to break the communication by making this SINR less than this threshold. In particular, we focus on investigating how incomplete information about the adversary’s location can impact the rival’s strategies. Namely, we assume that the transmitter does not know the adversary’s location, but knows only an a priori distribution of possible adversary locations. The problem is formulated as a non-zero Bayesian game between the transmitter and the adversary in a Nash and Stackelberg framework for Rayleigh channel fading gains. Existence and uniqueness of both type of equilibria are proven and derived in closed form. We prove theoretically, and numerically illustrate, that the Stackelberg equilibrium strategy for the transmitter can be non-sensitive to the a priori information, while the Nash equilibrium strategy for the transmitter is always sensitive to such information. The condition when the Stackelberg transmitter equilibrium strategy is non-sensitive to a priori information is derived.

In this paper we consider how subjectivity affects the problem of scanning spectrum bands, and the impact on both the scanner and invader’s strategy. To model such subjective behavior, we formulate a prospect theoretical (PT) extension of the Bayesian bandwidth scanning game where the Scanner knows only a priori probabilities about what type of intrusion (e.g. regular intensity or low intensity) occurs in the spectrum bands. Existence and uniqueness of the PT Bayesian equilibrium is proven. Moreover, these PT Bayesian equilibrium strategies are derived in closed form as functions of the detection probabilities associated with different invader types. Waterfilling equations are derived, which allows one to determine these detection probabilities. Bands where the Invader’s strategies have band-sharing form are identified. The sensitivity of the strategies to the subjective factors and a priori probabilities are numerically illustrated.

In this paper, we investigate a dilemma of employing silent mode and communication mode by an unmanned aerial vehicle (UAV) in communication with its controller. In many applications, a UAV communicates with a controller to receive instructions or accurate positioning, but such active communication poses a threat that the UAV can be hijacked through spoofing. On the other hand, during a silent mode (when the UAV does not communicate with the controller), the UAV is safe from spoofing, but is not receiving updates or other important data, and can degrade the overall UAV mission. To gain insight into the UAV risk versus benefit tradeoff, a simple game-theoretic model is presented. Additionally, this paper investigates how incomplete information about the capability of the controller to quickly learn the adversary’s attack and adjust its strategy accordingly can impact the equilibrium strategies. In contrast to regular-type capability, when both the rivals maximize their payoffs simultaneously, the capability of the controller to quickly learn is modeled by having the controller apply the best-response strategy. We model this problem using a Bayesian game, where the adversary knows only a priori probabilities about what capability the controller has. Dependence of the equilibrium strategies on these a priori probabilities is 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.

In this paper, we consider the problem of finding 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. Our model explores the uncertainty of the jammer’s location by assuming the joint system knows only the a priori probabilities of jammer’s positions. The underlying problem is formulated and solved as a Bayesian game involving the joint radar/communication system and a jammer. We then explore how irrational behavior by the rivals can affect the equilibrium strategies by using prospect theory (PT). It is shown that the PT system strategy is not sensitive to the jammer’s probability weighting parameter, while jammer’s strategy is sensitive to probability weighted parameters of both rivals.

The performance and resilience of communication networks is intimately tied to their underlying topological structure. Networks whose topological graphs do not exhibit sufficient interconnection are brittle and can be easily broken by network attacks that break links or remove nodes from the network. In this chapter, we explore the notion of network connectivity as quantified by the Fiedler value. We illustrate how it can be used by an adversary to determine locations where to attack a communication network and, conversely, how it can be used by network defense protocols to strengthen the network, thereby providing resilience to network attacks.

The paper considers a communication system consisting of a communication node utilizing multiple antennas in order to communicate with a group of receivers, while potentially facing interference from one or more jammers. The jammers impact the scenario by possibly interfering some of the receivers. The objective of the jammers is to reduce the throughput of nearby receivers, while taking into account the cost/risk of jamming. The fact that jammers face a cost implies that they might not choose to interfere, and thus the communication node faces uncertainty about which of its receivers will be jammed. This uncertainty is modeled by the communicator having only a priori probabilities about whether each receiver will face hostile interference or not, and if he does face such jamming, whether the jamming attack is smart or not. The goal of the communication node is to distribute total power resources to maximize the total throughput associated with communicating with all of the receivers. The problem is formulated as a Bayesian game between the communication system and the jammers. A waterfilling equation to find the equilibrium is derived, and its uniqueness is proven. The threshold value on the power budget is established for the receivers to be non-altruistic.

In this paper, we consider a two-hop network with a source node (SN) and a relay node (RN) who want to communicate data to a destination node (DN). The SN cannot be directly connected to the DN, but rather is connected only via the RN. The RN does not have an external source of energy, and thus needs to harvest energy from the SN to communicate, while the SN has an external source of energy and can harvest energy straight from it. Thus, a dilemma for the SN arises: how much to share harvested energy with the RN to make it relay the SN’s data to the DN. Fair performing of their communication tasks is considered as an incentive for the SN and the RN to cooperate. The optimal \(\alpha \) fair schedule is found for each \(\alpha \). It is shown that an altruistic strategy for one of the nodes comes in as a part of the cooperative solution (corresponding \(\alpha =0\)), while the maxmin strategy (corresponding \(\alpha \) tending to infinity) is proved to be egalitarian. Using Nash bargaining over the obtained continuum of fair solutions, we design a trade-off strategy.

The vast scale of the Internet of Things (IoT), combined with its heterogeneous nature involving many different types of devices and machines, could lead the IoT to be vulnerable to a variety of security threats and malicious attacks. Addressing the broad array of threats requires that different security mechanisms are deployed at appropriate locations within the broader IoT communication network. In this paper, we examine this problem by applying a resource allocation approach involving a game-theoretical framework to model: (a) an attack aimed to maximize total damage to the network, and (b) an attack aimed to compromise at least one of the devices. To evaluate the probability of a successful attack we apply a contest success function, and found the associated equilibrium strategies in closed form. Additionally, we note an interesting relationship between equilibrium strategies in security reinforcement games and OFDM transmission games under hostile jamming. A criteria is designed that allows one to determine whether an IoT controller’s resources is sufficient to protect all of the IoT devices it manages.

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.

Sharing of radio spectrum between different types of wireless systems (e.g., different service providers) is the foundation for making more efficient usage of spectrum. Cognitive radio technologies have spurred the design of spectrum servers that coordinate the sharing of spectrum between different wireless systems. These servers receive information regarding the needs of each system, and then provide instructions back to each system regarding the spectrum bands they may use. This sharing of information is complicated by the fact that these systems are often in competition with each other: each system desires to use as much of the spectrum as possible to support its users, and each system could learn and harm the bands of the other system. Three problems arise in such a spectrum-sharing problem: (1) how to maintain reliable performance for each system-shared resource (licensed spectrum); (2) whether to believe the resource requests announced by each agent; and (3) if they do not believe, how much effort should be devoted to inspecting spectrum so as to prevent possible malicious activity. Since this problem can arise for a variety of wireless systems, we present an abstract formulation in which the agents or spectrum server introduces obfuscation in the resource assignment to maintain reliability. We derive a closed form expression for the expected damage that can arise from possible malicious activity, and using this formula we find a tradeoff between the amount of extra decoys that must be used in order to support higher communication fidelity against potential interference, and the cost of maintaining this reliability. Then, we examine a scenario where a smart adversary may also use obfuscation itself, and formulate the scenario as a signaling game, which can be solved by applying a classical iterative forward-induction algorithm. For an important particular case, the game is solved in a closed form, which gives conditions for deciding whether an agent can be trusted, or whether its request should be inspected and how intensely it should be inspected.

The Internet of Things (IoT) is a recent trend that extends the boundary of the Internet to include a wide variety of computing devices. Connecting many stand-alone IoT systems through the Internet introduces many challenges, with security being front-and-center since much of the collected information will be exposed to a wide and often unknown audience. Unfortunately, due to the intrinsic capability limits of low-end IoT devices, which account for a majority of the IoT end hosts, many traditional security methods cannot be applied to secure IoT systems, which open a door for attacks and exploits directed both against IoT services and the broader Internet. This paper addresses this issue by introducing a unified IoT framework based on the MobilityFirst future Internet architecture that explicitly focuses on supporting security for the IoT. Our design integrates local IoT systems into the global Internet without losing usability, interoperability and security protection. Specifically, we introduced an IoT middleware layer that connects heterogeneous hardware in local IoT systems to the global MobilityFirst network. We propose an IoT name resolution service (IoT-NRS) as a core component of the middleware layer, and develop a lightweight keying protocol that establishes trust between an IoT device and the IoT-NRS.

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.

This paper examines a dual radar/communication system employing OFDM style waveforms with two objectives: a radar task involving target tracking, and a communication task involving communicating with a distant receiver. One challenge with such two objective problems is that the optimal solution for one of objective could be non-optimal for the other. We examine the problem of resolving dual radar/communication objectives and solve the associated two objective problem in two steps: First, for each fixed level of performance for the radar’s objective, the optimal solution is found in a water-filling form which includes the classical OFDM waterfilling solution as a boundary case. The formulation returns a continuum of optimal solutions (a solution per radar performance level). Second, from this continuum of solutions, we find the Nash bargaining solution, which returns the best tradeoff between the two objectives, and an algorithm to find the Nash bargaining solution is presented.

Wireless networks are increasingly moving towards a heterogeneous operating model involving the sharing of spectrum resources by different access technologies. Sharing wireless resources between different wireless technologies requires protocols that share spectrum in an equitable manner. In this paper, we examine the time-sharing of wireless channels by Wi-Fi and LTE-U networks. To design fair access protocol for the networks we use \(\alpha \) fairness criterion. It allows to find a continuum of fair protocols (a protocol per \(\alpha \)). To find the most fair from this continuum of fair protocols we apply Nash bargaining approach. In particular, we show that such a time-sharing bargaining protocol, in spite of the interference between signals, can lead to a gain for both networks under an increase of the transmission power to one of them.

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.

Cybersecurity is critical to society at large, and its importance is growing daily. The rapid advancement in technology has caused a large-scale integration of computing, communication, and information technologies into virtually every aspect of our modern society[...]

The paper is concerned with the problem Wi-Fi and LTE-U networks sharing access to a band of communication channels, while also considering the issue of fairness in how the channel is being shared. As a criteria of fairness for such joint access, \(\alpha \)-fairness and maxmin fairness with regards to expected throughput are explored as fairness metrics. Optimal solutions are found in closed form, and it is shown that these solutions can be either: (a) a channel on/off strategy in which access to the channels is performed sequentially, or (b) a channel sharing strategy, i.e., where simultaneous joint access to the channels is applied. A criteria for switching between these two type of optimal strategies is found, and its robustness on the fairness coefficient is established, as well as the effectiveness of the fairness coefficient to control the underlying protocol of the joint access to the shared resource is managed. Finally, we note that the approach that is explored is general, and it might be adapted to different problems for accessing a sharing resource, like joint sharing of voice and data traffic by cellular carriers.