Explainable AI-Based Intrusion Detection Systems for IoT Environments: A Systematic Literature Review. [PDF]
Varol M, Karakaya A.
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A Blockchain-Enabled Security Framework for Cloud-Based Sensor Systems with Deep Learning-Driven Attack Classification. [PDF]
Ahmad N, Cao Y, Liu W.
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Resilient fractional order sliding mode control for islanded microgrids under cyber-physical attacks. [PDF]
Ibraheem MI +4 more
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A novel intrusion detection system for IIoT in 5G networks using attention-augmented federated learning and lightweight transformer architectures. [PDF]
Du J.
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Data-Driven False Data Injection Attack: A Low-Rank Approach
IEEE Transactions on Smart Grid, 2022False data injection attack on the state estimation algorithms have already showcased its detrimental effects for modern grid operation. This letter promotes a novel attack vector formulation policy for the linear state estimation algorithm by exploring ...
Debottam Mukherjee
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Summation Detector for False Data-Injection Attack in Cyber-Physical Systems
IEEE Transactions on Cybernetics, 2020In this paper, from the perspectives of defenders, we consider the detection problems of false data-injection attacks in cyber-physical systems (CPSs) with white noise. The false data-injection attacks usually modify the sensor data to make CPSs unstable
Dan Ye, Tian-Yu Zhang
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Kinematic Control of Serial Manipulators Under False Data Injection Attack
IEEE/CAA Journal of Automatica Sinica, 2023With advanced communication technologies, cyber-physical systems such as networked industrial control systems can be monitored and controlled by a remote control center via communication networks.
Yinyan Zhang
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Detection, estimation, and compensation of false data injection attack for UAVs
Information Sciences, 2021The safety issues of unmanned aerial vehicles (UAVs) are ever increasing in focus due to the vulnerability to attack. This paper investigates the safety problem for UAVs under the false data injection attack (FDIA) through wireless data link.
Kexin Guo, Xiang Yu, Jianzhong Qiao
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False data injection attacks are commonly used to evade the bad data detector in cyber-physical power systems. This paper proposes an extended attack strategy and a deep reinforcement learning-based detection method.
Xiaohong Ran
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