Optimal transmission strategy for sensors to defend against eavesdropping and jamming attacks

Yuan, Li; Wang, Kun; Miyazaki, Toshiaki; Guo, Song; Wu, Meng

doi:10.1109/icc.2017.7996845

Cited by 13 publications

(4 citation statements)

References 23 publications

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“…The channel is assumed to be flat fading. As examples of studying single carrier communication, see, for example, [1,4,7,8,10,13,14,[17][18][19][20]. We assume that the user does not have access to local information about the jammer's channel gain (reflecting its distance to the receiver) and jamming power cost (reflecting technical characteristics of the jammer).…”

Section: Communication Modelmentioning

confidence: 99%

A Non-zero Sum Power Control Game with Uncertainty

Garnaev

2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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We consider the communication between a transmitter (user) and a receiver in the presence of a jammer where the jammer, in contrast to the user, has access to local information about jamming fading gain (reflecting distance of the jammer to the receiver) and jamming cost (reflecting its technical characteristics). The problem is modeled as a Bayesian game. Signal-to-interference-plus-noise ratio (SINR) is considered as user's communication utility. Nash equilibrium as well as Stackelberg equilibrium are derived in closed form and compared.

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Section: Communication Modelmentioning

confidence: 99%

A Non-zero Sum Power Control Game with Uncertainty

Garnaev

2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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“…A fictitious play-based algorithm was proposed to assist in reaching the mixed strategy Nash equilibrium, and results show that an improvement can be achieved in the average expected utility per user up to 49.4%. Moreover, eavesdropping and jamming attacks on mobile Cyber-Physical Systems (CPSs) were studied in [17], where a Stackelberg game was used to maximize the secrecy rate between sensors and controllers. Recently, a new approach that considers a more sophisticated adversary with dual capability of conducting either eavesdropping or jamming attack has been proposed in [9].…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Provoking the Adversary by Detecting Eavesdropping and Jamming Attacks: A Game‐Theoretical Framework

Salem

Liao

Shen

et al. 2018

Wireless Communications and Mobile Computing

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This paper investigates the secrecy and reliability of a communication where the user is assisting an Intrusion Detection System (IDS) in detecting the adversary’s attack. The adversary is assumed to be sophisticated such that it can conduct eavesdropping and jamming attacks. The IDS is equipped with the capability of detecting both of those attacks. Two scenarios were considered; the first scenario is that the user is trying to detect the adversary by assisting the IDS, and the second scenario is that the user is equipped with a silent time slot in its communication protocol besides assisting the IDS, in order to provoke the adversary into jamming the channel, thus detecting it with a higher probability. Interestingly, adding the capability of detecting eavesdropping attacks pushed the adversary into conducting jamming attacks much more, thus aiding in detecting the adversary earlier. All of that was modeled by means of stochastic game theory, in order to analyze and study the behavior and the interactions between the user and the adversary. Results show a major improvement in the first scenario by 188% and an improvement by 294% in the second scenario in the game value when the probability of detecting eavesdropping attacks was 0.3, which represents the payoff that the user gains in terms of secrecy and reliability.

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“…Yuan [29] transformed the system model into MDP in order to obtain the optimal transmission scheduling to minimize the AoI of CPS and keep the AoI of eavesdroppers above a certain level, and proved that the optimal transmission scheduling strategy is a threshold behavior on the CPS and AoI of eavesdroppers, respectively. In [30], the proposed problem is formulated as a Stackelberg game, and the strategy of maximizing the secure transmission rate between sensor and controller in the presence of malicious eavesdroppers and disruptors is studied. On the basis of analyzing the influence of different strategies on eavesdropping performance, Zhou [31] studied the multi-output system and proposed a decryption scheduling scheme to minimize the expected estimation error under the condition of energy constraint.…”

Section: Introductionmentioning

confidence: 99%

Allocation of Eavesdropping Attacks for Multi-System Remote State Estimation

Chang,

Peng,

Zhang

2024

Sensors

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In recent years, the problem of cyber–physical systems’ remote state estimations under eavesdropping attacks have been a source of concern. Aiming at the existence of eavesdroppers in multi-system CPSs, the optimal attack energy allocation problem based on a SINR (signal-to-noise ratio) remote state estimation is studied. Assume that there are N sensors, and these sensors use a shared wireless communication channel to send their state measurements to the remote estimator. Due to the limited power, eavesdroppers can only attack M channels out of N channels at most. Our goal is to use the Markov decision processes (MDP) method to maximize the eavesdropper’s state estimation error, so as to determine the eavesdropper’s optimal attack allocation. We propose a backward induction algorithm which uses MDP to obtain the optimal attack energy allocation strategy. Compared with the traditional induction algorithm, this algorithm has lower computational cost. Finally, the numerical simulation results verify the correctness of the theoretical analysis.

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Optimal transmission strategy for sensors to defend against eavesdropping and jamming attacks

Cited by 13 publications

References 23 publications

A Non-zero Sum Power Control Game with Uncertainty

A Non-zero Sum Power Control Game with Uncertainty

Provoking the Adversary by Detecting Eavesdropping and Jamming Attacks: A Game‐Theoretical Framework

Allocation of Eavesdropping Attacks for Multi-System Remote State Estimation

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