Energy Absorbable Optimal DoS Attack Strategy for Remote State Estimation in CPSs With Two-Hop Networks

• Published in: IEEE access Vol. 12; pp. 195866 - 195874
• Main Authors: Gao, Jinfang, Huang, Tao, Xing, Wei, Han, Xiumei
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Batteries; Communications systems; Cyber-physical systems; Denial of service attacks; Denial-of-service attack; DoS attacks; Error analysis; Intelligent sensors; Interference; Machine learning; Markov processes; Multiagent systems; Noise; Optimization; power strategies; Relays; Sensors; State estimation; two-hop networks; Wireless communication; Wireless communications; Wireless sensor networks
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2024.3520821

This paper focuses on the investigation of optimal attack power strategies in cyber-physical systems with a two-hop network subject to two malicious attackers. The objective is to analyze the effects of DoS attacks on wireless communication channels, specifically targeting the degradation of the system's estimation performance. The attackers can exploit energy from the surrounding environment and employ it to interfere with the communication of information from the sensor to the remote estimator. Both attackers share the same goal of maximizing the error covariance at the remote estimator during the transmission process. To address this problem, we formulate it as a multi-agent markov decision process (MAMDP) and proposed a Q-learning algorithm to determine the optimal attack power strategies. The work provides insights into effective strategies for countering the attackers' disruptive actions and mitigating the impact on the system's estimation performance. Finally, simulation examples are offered to validate and demonstrate the theoretical results.