Can I read Vulnerability Identification and Remediation of FDI Attacks in Islanded DC Microgrids Using Multiagent Reinforcement Learning on EtoBox?

Vulnerability Identification and Remediation of FDI Attacks in Islanded DC Microgrids Using Multiagent Reinforcement Learning by Ali Jafarian Abianeh; Yihao Wan; Farzad Ferdowsi; Nenad Mijatovic; Tomislav Dragicevic is a Engineering article available to read on EtoBox.

What is Vulnerability Identification and Remediation of FDI Attacks in Islanded DC Microgrids Using Multiagent Reinforcement Learning about?

This article proposes a novel approach to uncover deficiencies of the existing cyber-attack detection schemes and thereby to serve as a foundation for establishing more reliable cybersecure solutions, with particular application in dc microgrids. For this purpose, a multiagent deep reinforcement learning (RL)-based algorithm is proposed to automatically discover the vulnerable spots in the conventional index-based cyberattack detection schemes and automatically generate coordinated stealthy destabilizing false data injection (FDI) attacks on cyber-protected islanded dc microgrids. To enable a continuous action space for the trained RL agents and enhance the algorithm's precision and convergence rate, deep deterministic policy gradient is incorporated. Using this approach, susceptibility of a state-of-the-art detection scheme to several different coordinated FDI attacks on the distributed communication links is identified. The proposed algorithm is also enhanced with a sniffing feature to enable maintaining the stealthy attacks even under the sudden disconnection of any of the compromised links. To address the discovered deficiencies within the index-based detection scheme, a comple

Who reads Vulnerability Identification and Remediation of FDI Attacks in Islanded DC Microgrids Using Multiagent Reinforcement Learning?

Author

Ali Jafarian Abianeh; Yihao Wan; Farzad Ferdowsi; Nenad Mijatovic; Tomislav Dragicevic

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Published

2022

Language

EN

Field

Engineering (Physical Sciences)