Detecting Generalized Replay Attacks via Time-Varying Dynamic Watermarking

TL;DR

This paper extends dynamic watermarking techniques to linear time-varying systems, enabling detection of generalized replay attacks in complex cyber-physical systems like autonomous vehicles.

Contribution

It introduces a matrix normalization factor for LTV systems and demonstrates its effectiveness in detecting replay attacks.

Findings

Successfully detects replay attacks in LTV vehicle models.

Provides implementable tests for real-world systems.

Extends dynamic watermarking to more complex, time-varying models.

Abstract

Cyber-physical systems (CPS) often rely on external communication for supervisory control or sensing. Unfortunately, these communications render the system vulnerable to cyber-attacks. Attacks that alter messages, such as replay attacks that record measurement signals and then play them back to the system, can cause devastating effects. Dynamic Watermarking methods, which inject a private excitation into control inputs to secure resulting measurement signals, have begun addressing the challenges of detecting these attacks, but have been restricted to linear time invariant (LTI) systems. Though LTI models are sufficient for some applications, other CPS, such as autonomous vehicles, require more complex models. This paper develops a linear time-varying (LTV) extension to previous Dynamic Watermarking methods by designing a matrix normalization factor to accommodate the temporal changes in the system. Implementable tests are provided with considerations for real-world systems. The proposed method is then shown to be able to detect generalized replay attacks both in theory and in simulation using a LTV vehicle model.