Visible to the public Biblio

Filters: Author is Amin Ghafouri  [Clear All Filters]
Journal Article
Amin Ghafouri, Yevgeniy Vorobeychik, Xenofon D. Koutsoukos.  2018.  Adversarial Regression for Detecting Attacks in Cyber-Physical Systems. CoRR. abs/1804.11022

Attacks in cyber-physical systems (CPS) which manipulate sensor readings can cause enormous physical damage if undetected. Detection of attacks on sensors is crucial to mitigate this issue. We study supervised regression as a means to detect anomalous sensor readings, where each sensor's measurement is predicted as a function of other sensors. We show that several common learning approaches in this context are still vulnerable to \emph{stealthy attacks}, which carefully modify readings of compromised sensors to cause desired damage while remaining undetected. Next, we model the interaction between the CPS defender and attacker as a Stackelberg game in which the defender chooses detection thresholds, while the attacker deploys a stealthy attack in response. We present a heuristic algorithm for finding an approximately optimal threshold for the defender in this game, and show that it increases system resilience to attacks without significantly increasing the false alarm rate.