Data-Injection Attacks in Stochastic Control Systems: Detectability and Performance Tradeoffs
Optimization and Control
2017-04-05 v1 Systems and Control
Abstract
Consider a stochastic process being controlled across a communication channel. The control signal that is transmitted across the control channel can be replaced by a malicious attacker. The controller is allowed to implement any arbitrary detection algorithm to detect if an attacker is present. This work characterizes some fundamental limitations of when such an attack can be detected, and quantifies the performance degradation that an attacker that seeks to be undetected or stealthy can introduce.
Cite
@article{arxiv.1704.00748,
title = {Data-Injection Attacks in Stochastic Control Systems: Detectability and Performance Tradeoffs},
author = {Cheng-Zong Bai and Fabio Pasqualetti and Vijay Gupta},
journal= {arXiv preprint arXiv:1704.00748},
year = {2017}
}