IRS-Assisted Proactive Eavesdropping Over Fading Channels Based on Deep Reinforcement Learning

Li, Baogang; Cui, Kangjia

doi:10.1109/lcomm.2022.3175222

Cited by 7 publications

(2 citation statements)

References 19 publications

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“…The authors in [37] optimized the energy problem for the proactive eavesdropping systems. The work in [38] used the deep reinforcement learning optimization way to study the influence of RIS on proactive eavesdropping networks. In [39], the location and power were both optimized for the eavesdropping networks in the presence of a fullduplex forward relay.…”

Section: B Motivationsmentioning

confidence: 99%

Proactive Eavesdropping Performance for Integrated Satellite–Terrestrial Relay Networks

Wu,

Guo,

et al. 2023

IEEE Open J. Commun. Soc.

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This paper studies the performance for the proactive eavesdropping-based legitimate surveillance for the integrated satellite-terrestrial relay networks in the presence of several monitors. To investigate the proactive eavesdropping performance, we propose three different presentative proactive eavesdropping cases/modes. In these cases, the monitors can chose its roles, i.e., the eavesdroppers or jammers. On this foundation, three cases are considered in this paper, namely, Case I: Eavesdropping then Jamming, Case II: Jamming then Eavesdropping, Case III: Always Eavesdropping. Especially, the exact expressions for the eavesdropping non-outage probability for the considered three modes are obtained. Besides, the asymptotic expressions for the eavesdropping non-outage probability are further derived based on the three proposed cases. In addition, the colluding proactive eavesdropping algorithm is utilized in the considered proactive network, which means all the monitors works together to steal the information or jam the users. At last, some Monte Carlo results are given to confirm the validity of the theoretical results.

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Section: B Motivationsmentioning

confidence: 99%

Proactive Eavesdropping Performance for Integrated Satellite–Terrestrial Relay Networks

Wu,

Guo,

et al. 2023

IEEE Open J. Commun. Soc.

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“…The PLS enhancement was validated through simulation results. The RL was utilized to maximize the eavesdropping rate in [297] in the presence of legitimate RIS to assess the eavesdropping performance. The authors in [247] utilized the multi-agent DRL-based technique to design RIS reflection coefficients and relay selection to secure buffer-aided cooperative networks.…”

Section: A Deep Reinforcement Learningmentioning

confidence: 99%

Relay Selection for Improving Physical Layer Security in D2D Underlay Communications

2022

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This paper investigates the physical layer security of inband underlay Device-to-Device (D2D) communication, where the direct link between D2D users is not available. In this respect, optimal relay and suboptimal relay selections are utilized to secure the D2D transmission. The eavesdropper uses either maximal-ratio combining or selection combining to increase the wiretapped signals. The D2D secrecy performance analysis is performed regarding the secrecy outage probability (SOP) and the probability of non-zero secrecy capacity, and closed-form expressions are provided for both relay selection approaches and verified using Monte-Carlo simulation. From the numerical results, it is shown that increasing the number of D2D relays enhances the secrecy performance of D2D communications. Moreover, the exact asymptotic analysis of the SOP is provided. It turns out that the diversity order of both relay selection approaches is the same.INDEX TERMS Physical layer security, D2D communications, secrecy outage probability, optimal and suboptimal relay selection, maximal-ratio combining, and selection combining., 1

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Artificial intelligence empowered physical layer security for 6G: State-of-the-art, challenges, and opportunities

Zhang,

Zhu,

Liu

2024

Computer Networks

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IRS-Assisted Proactive Eavesdropping Over Fading Channels Based on Deep Reinforcement Learning

Cited by 7 publications

References 19 publications

Proactive Eavesdropping Performance for Integrated Satellite–Terrestrial Relay Networks

Proactive Eavesdropping Performance for Integrated Satellite–Terrestrial Relay Networks

Relay Selection for Improving Physical Layer Security in D2D Underlay Communications

Artificial intelligence empowered physical layer security for 6G: State-of-the-art, challenges, and opportunities

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