Monitoring in the Dark: Privacy-Preserving Runtime Verification of Cyber-Physical Systems
Charles Koll, Preston Tan Hang, Mike Rosulek, Houssam Abbas

TL;DR
This paper introduces a privacy-preserving protocol for runtime verification of Cyber-Physical Systems using garbled circuits, ensuring confidentiality of both measurements and specifications during monitoring.
Contribution
It presents a novel protocol that enables privacy-preserving robustness monitoring in Cyber-Physical Systems using garbled circuits for Signal Temporal Logic specifications.
Findings
The protocol maintains privacy of signals and specifications.
Analysis shows acceptable runtime and memory overhead.
Practical for design testing, offline, and online monitoring scenarios.
Abstract
In distributed Cyber-Physical Systems and Internet-of-Things applications, the nodes of the system send measurements to a monitor that checks whether these measurements satisfy given formal specifications. For instance in Urban Air Mobility, a local traffic authority will be monitoring drone traffic to evaluate its flow and detect emerging problematic patterns. Certain applications require both the specification and the measurements to be private -- i.e. known only to their owners. Examples include traffic monitoring, testing of integrated circuit designs, and medical monitoring by wearable or implanted devices. In this paper we propose a protocol that enables privacy-preserving robustness monitoring. By following our protocol, both system (e.g. drone) and monitor (e.g. traffic authority) only learn the robustness of the measured trace w.r.t. the specification. But the system learns…
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Taxonomy
TopicsFormal Methods in Verification · Security and Verification in Computing · Adversarial Robustness in Machine Learning
