Relational Analysis of Sensor Attacks on Cyber-Physical Systems
Jian Xiang, Nathan Fulton, Stephen Chong

TL;DR
This paper introduces a formal framework using hybrid programs to analyze sensor attack impacts on cyber-physical systems, focusing on their robustness and safety under attack scenarios.
Contribution
It develops a formal method for modeling and verifying sensor attack effects on cyber-physical systems, including novel proof techniques for relational properties.
Findings
Framework successfully models sensor attack impacts
Proof techniques decompose complex verification tasks
Case studies demonstrate practical applicability
Abstract
Cyber-physical systems, such as self-driving cars or autonomous aircraft, must defend against attacks that target sensor hardware. Analyzing system design can help engineers understand how a compromised sensor could impact the system's behavior; however, designing security analyses for cyber-physical systems is difficult due to their combination of discrete dynamics, continuous dynamics, and nondeterminism. This paper contributes a framework for modeling and analyzing sensor attacks on cyber-physical systems, using the formalism of hybrid programs. We formalize and analyze two relational properties of a system's robustness. These relational properties respectively express (1) whether a system's safety property can be influenced by sensor attacks, and (2) whether a system's high-integrity state can be affected by sensor attacks. We characterize these relational properties by defining…
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Taxonomy
TopicsSecurity and Verification in Computing · Advanced Malware Detection Techniques · Physical Unclonable Functions (PUFs) and Hardware Security
