Spatial Anti-Jamming Scheme for Internet of Satellites Based on the Deep Reinforcement Learning and Stackelberg Game

Han, Chen; Huo, Liangyu; Tong, Xinhai; Wang, Haichao; Liu, Xian

doi:10.1109/tvt.2020.2982672

Cited by 73 publications

(40 citation statements)

References 35 publications

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“…Digital currency design for debris removal [61] Multi-sensor space debris tracking [62] Reinforcement learning for debris removal [63] Multibistatic radar [64] Space Debris Reconfiguration through remote uplink [56] Periodic reconfigura -tion [57] SEU TMR [58] Fault-tolerant Viterbi decoder [59] Fault-tolerant Turbo decoder [60] Robust constrained inverse BF [52] Jamming Anti-jamming based on IRS [54] DRL and stackelberg game [53] Satellite diversity [55] Coverageexpanding [48] Inter-system interference REM based spectrum sensing [50] Heuristics based RRM [49] SIC [51] Shortest path routing with risk control [44] Node compromise Stochastic blockchain [45] Artificial neural networks based intrusion detection [46] Physical unclonable password [47] Vulnerability intelligent early warning [41] Hijacking Big Data-aided intrusion detection [42] ROAchain based on blockchain [43] Robust BF [38] Wiretap Threshold-based Scheduling [39] IRS [40] Fig. 3: Development timeline of related works for solving security vulnerabilities.…”

Section: 2021mentioning

confidence: 99%

See 1 more Smart Citation

On the Security of LEO Satellite Communication Systems: Vulnerabilities, Countermeasures, and Future Trends

Yue¹,

An²,

Zhang³

et al. 2022

Preprint

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Section: 2021mentioning

confidence: 99%

“…ment Learning (DRL) and Stackelberg game-assisted spatial anti-jamming was proposed by Han et al [53] for the Internet of Satellites. The communication countermeasures protecting satellite users against jammers were modeled as a Stackelberg anti-jamming routing game.…”

Section: 2021mentioning

confidence: 99%

On the Security of LEO Satellite Communication Systems: Vulnerabilities, Countermeasures, and Future Trends

Yue¹,

An²,

Zhang³

et al. 2022

Preprint

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show abstract

“…The authors successfully use Q-learning algorithm in order to find a suboptimal satellite strategy in an unknown jamming environment. In [12], the authors apply deep reinforcement learning to find a satellite routing scheme and a fast response anti-jamming algorithm.…”

Section: Introductionmentioning

confidence: 99%

Jamming and Anti-Jamming Strategies of Mobile Vehicles

Dubosarskii

Primak

2021

Electronics

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Anti-jamming games have become a popular research topic. However, there are not many publications devoted to such games in the case of vehicular ad hoc networks (VANETs). We considered a VANET anti-jamming game on the road using a realistic driving model. Further, we assumed the quadratic power function in both vehicle and jammer utility functions instead of the standard linear term. This makes the game model more realistic. Using mathematical methods, we expressed the Nash equilibrium through the system parameters in single-channel and multi-channel cases. Since the network parameters are usually unknown, we also compared the performance of several reinforcement learning algorithms that iteratively converge to the Nash equilibrium predicted analytically without having any information about the environment in the static and dynamic scenarios.

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“…While considering the existence of malicious jamming attacks, Stackelberg game [14][15][16][17][18][19][20][21][22][23][24] is a suitable game model to formulate the competitive interactions between the user-side and the jammer-side as it can well depict the sequential decision-making relationship between two countermeasure sides. For example, authors in [14] considered the anti-jamming power control problem with observation error, and derived the Stackelberg equilibrium (SE) of the proposed Stackelberg game.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Coordinated Anti-Jamming Channel Access in Clustering Networks: A Multi-Leader Multi-Follower Stackelberg Game Approach

Chen

Feng

et al. 2021

Preprint

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This paper mainly investigates the multi-user coordinated anti-jamming problem in clustering communication networks. In such kinds of networks, there exist multiple clusters, and multiple users who communicate with their receivers simultaneously. Besides, a malicious jammer persistently attacks channels with wide-band and dynamic changing jamming signals. To cope with these challenges brought by the large-scale clustering network and the dynamic wide-band jamming, a hierarchical coordinated anti-jamming approach is proposed, and a multi-leader multi-follower Stackelberg game is introduced to model the anti-jamming problem. In detail, cluster heads act as leaders, and select available frequency bands to avoid jamming attacks. While users in each cluster act as followers, and select corresponding channels distributedly and independently. Moreover, it is proved that there exist multiple Stackelberg Equilibriums (SEs) in the proposed game. To obtain SEs, a hierarchical coordinated anti-jamming channel access (HCACA) algorithm is designed. Simulation results illustrate that the proposed approach is effective to cope with the dynamic wide-band jamming attacks. Furthermore, it is also depicted that the proposed approach outperforms the distributed anti-jamming comparative approach in terms of convergence speed.

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Spatial Anti-Jamming Scheme for Internet of Satellites Based on the Deep Reinforcement Learning and Stackelberg Game

Cited by 73 publications

References 35 publications

On the Security of LEO Satellite Communication Systems: Vulnerabilities, Countermeasures, and Future Trends

On the Security of LEO Satellite Communication Systems: Vulnerabilities, Countermeasures, and Future Trends

Jamming and Anti-Jamming Strategies of Mobile Vehicles

Hierarchical Coordinated Anti-Jamming Channel Access in Clustering Networks: A Multi-Leader Multi-Follower Stackelberg Game Approach

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