Safety monitoring under stealthy sensor injection attacks using reachable sets

TL;DR

This paper proposes a method to detect stealthy sensor injection attacks in industrial plants by monitoring control inputs and computing reachable sets using convex optimization, enhancing security without relying on traditional fault detectors.

Contribution

It introduces a novel approach to detect stealthy attacks by calculating ellipsoidal bounds of input reachable sets through convex optimization.

Findings

Effective detection of stealthy sensor attacks in simulation

Ellipsoidal bounds successfully identify attack-driven critical states

Method enhances security monitoring in industrial control systems

Abstract

Stealthy sensor injection attacks are serious threats for industrial plants as they can compromise the plant's integrity without being detected by traditional fault detectors. In this manuscript, we study the possibility of revealing the presence of such attacks by monitoring only the control input. This approach consists in computing an ellipsoidal bound of the input reachable set. When the control input does not belong to this set, this means that a stealthy sensor injection attack is driving the plant to critical states. The problem of finding this ellipsoidal bound is posed as a convex optimization problem (convex cost with Linear Matrix Inequalities constraints). Our monitoring approach is tested in simulation.