Invisible Manipulation: Deep Reinforcement Learning-Enhanced Stealthy Attacks on Battery Energy Management Systems

Invisible Manipulation: Deep Reinforcement Learning-Enhanced Stealthy Attacks on Battery Energy Management Systems

This paper introduces an innovative cyber-attack scheme, “invisible manipulation,” utilizing timed-stealthy false data injection attacks (Timed-SFDIAs). By subtly altering critical measurements ahead of a target period, the attacker covertly steers system operations toward a sp...

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Bibliographic Details
Main Authors: Qi Xiao, Lidong Song, Jong Ha Woo, Rongxing Hu, Bei Xu, Kai Ye, Ning Lu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Cyber-physical attacks
deep reinforcement learning
timed stealthy false data injection (SFDIA)
invisible manipulation attacks
state-of-charge (SoC) estimation
Online Access:https://ieeexplore.ieee.org/document/11084779/
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https://ieeexplore.ieee.org/document/11084779/

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