Simulation and Real-World Evaluation of Attack Detection Schemes

Matthew Porter1, Arnav Joshi1, Pedro Hespanhol2, Anil Aswani2, Matthew Johnson-Roberson1, Ram Vasudevan3

  • 1University of Michigan
  • 2UC Berkeley
  • 3University of Michigan, Ann Arbor



Regular Session


10:00 - 12:00 | Wed 10 Jul | Room 407 | WeA16

Stochastic Systems

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A variety of anomaly detection schemes have been proposed to detect malicious attacks to Cyber-Physical Systems. Among these schemes, Dynamic Watermarking methods have been proven highly effective at detecting a wide range of attacks. Unfortunately, in contrast to other anomaly detectors, no method has been presented to design a Dynamic Watermarking detector to achieve a user-specified false alarm rate, or subsequently evaluate the capabilities of an attacker under such a selection. This paper describes methods to measure the capability of an attacker, to numerically approximate this metric, and to design a Dynamic Watermarking detector that can achieve a user-specified rate of false alarms. The performance of the Dynamic Watermarking detector is compared to three classical anomaly detectors in simulation and on a real-world platform. These experiments illustrate that the attack capability under the Dynamic Watermarking detector is comparable to those of classic anomaly detectors. Importantly, these experiments also make clear that the Dynamic Watermarking detector is consistently able to detect attacks that the other class of detectors are unable to identify.

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