Prospect theoretic analysis of anti-jamming communications in cognitive radio networks

Xiao, Liang; Liu, Jinliang; Li, Yan; Mandayam, Narayan B.; Poor, H. Vincent

doi:10.1109/glocom.2014.7036897

Cited by 38 publications

(26 citation statements)

References 27 publications

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“…Problems related to spectrum scanning have been presented in [31,32], where the objective is to develop spectrum-scanning strategies that support the detection of a user illicitly using spectrum, and [33] for detecting attacks aimed at reducing the size of spectrum opportunities in a dynamic spectrum-sharing problem. [34] studied the interactions between a user and a smart jammer regarding their respective choices of transmit power in a general wireless setting, while [35,36] considered problems related to game theory and network security, While these references are not directly relevant to the spectrum allocation problem explored in this paper, these references help motivate the work that we present in this paper.…”

Section: Introductionmentioning

confidence: 94%

Competitive Sharing of Spectrum: Reservation Obfuscation and Verification Strategies

Garnaev

Trappe

2017

Entropy

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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.

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Section: Introductionmentioning

confidence: 94%

Competitive Sharing of Spectrum: Reservation Obfuscation and Verification Strategies

Garnaev

Trappe

2017

Entropy

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“…From (11), U j (Ps , Pr , P j ) is a concave function with re spect to p.. By setting (10) to 0, we can obtain P j =…”

Section: A Optimal Jamming Strategymentioning

confidence: 99%

“…For example, in [10], the wireless security problem was formulated as an indirect reciprocity game, where nodes applies the indirect reciprocity principle to suppress attacks in wireless networks. Assuming that end-user decision making is under uncertainty, the interactions between a user and a smart jammer were modeled as a game by using prospect theory in [11]. In addition, Yang et al studied power control problem with a smart jammer with a Stackelberg game in [12] and [13].…”

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confidence: 99%

Power control Stackelberg game in cooperative anti-jamming communications

Xiao

Liu

et al. 2014

The 2014 5th International Conference on Game Theory for Networks

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As wireless networks are vulnerable to malicious attacks, security issues have aroused enormous research interest.In this paper, we focus on the anti-jamming power control of transmitters in a cooperative wireless network attacked by a smart jammer with the capability to sense the ongoing transmis sion power before making a jamming decision. By modeling the interaction between transmitters and a jammer as a Stackelberg game, we analyze the optimal strategies for both transmitters and the jammer and thus derive the Stackelberg equilibrium of the game. In addition, the Nash equilibrium of the anti-jamming game is also derived to compare with the Stackelberg equilibrium strategy. Finally, the impacts of the fading channel gains of the transmitters and the jammer on their utilities and the SINR are measured, respectively. Simulation results are presented to verify the performance of the proposed Stackelberg equilibrium strategy.

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“…The authors investigate equilibrium points in the form of pure strategies [16]- [20] as well as mixed strategies [21], [22] and examine optimal power allocations that maximize the utility functions defined. Under the assumption of full knowledge of the system, the authors in [16] formulate a zero-sum power allocation game between a transmitter and a jammer and prove the existence of pure strategy Nash Equilibrium (NE) points and characterize them in the form of optimized secrecy capacity in the presence of a passive eavesdropper.…”

Section: A Related Workmentioning

confidence: 99%

Strategic Power Allocation With Incomplete Information in the Presence of a Jammer

El-Bardan¹,

Brahma²,

Varshney³

2016

IEEE Trans. Commun.

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In this paper, distributed competitive interactions between a secondary user (SU) transmitter-receiver pair and a jammer are investigated using a game-theoretic framework under physical interference restrictions, power budget constraints, and incomplete knowledge of channel gains. In this game, the SU transmitter is expected to choose its power strategy with the objective of satisfying a minimum signal-to-interference plus noise ratio (SINR) at the corresponding receiver. Similarly, the jammer's objective is to strategically allocate its power so that the SINR constraint of the SU is not satisfied. Due to a lack of complete information, this strategic power allocation problem between the two players is modeled as a Bayesian game for which the self-enforcing strategies of the SU transmitter-receiver pair and the jammer are analyzed. Furthermore, probability distributions are employed by the corresponding players to model the incomplete nature of the game. The solution of the game corresponds to Nash Equilibria (NE) points. Equilibrium analysis is carried out by considering the mixed strategy solution space and numerical examples are presented for illustration.

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Prospect theoretic analysis of anti-jamming communications in cognitive radio networks

Cited by 38 publications

References 27 publications

Competitive Sharing of Spectrum: Reservation Obfuscation and Verification Strategies

Competitive Sharing of Spectrum: Reservation Obfuscation and Verification Strategies

Power control Stackelberg game in cooperative anti-jamming communications

Strategic Power Allocation With Incomplete Information in the Presence of a Jammer

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