Detecting Generalized Replay Attacks via Time-Varying Dynamic Watermarking

• 成果类型: Article
• 署名作者: Porter, Matthew; Hespanhol, Pedro; Aswani, Anil; Johnson-Roberson, Matthew; Vasudevan, Ramanarayan
• 署名单位: University of Michigan System; University of Michigan; University of California System; University of California Berkeley; University of Michigan System; University of Michigan
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2020.3022756
• 发表日期: 2021
• 页码: 3502-3517
• 关键词: Watermarking; detectors; Linear systems; measurement; Vehicle dynamics; Time-varying systems; degradation; cyber-physical systems (CPS); Dynamic watermarking; linear time varying (LTV); networked control systems; secure control

摘要

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 article 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 an LTV vehicle model.