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Control Barrier Function-Based Attack Recovery With Provable Guarantees

delete2026-04-13
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PRE
AI
K
Kunal Garg
R
Ricardo G. Sanfelice
Á
Álvaro A. Cárdenas
DOI:10.1109/tac.2026.3683371delete
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Abstract

Abstract

En 中文
This article investigates security guarantees for cyber-physical systems (CPS) against actuator attacks. We introduce a new attack-detection mechanism based on zeroing control barrier function conditions. We propose an adaptive recovery mechanism that responds based on the system’s proximity to safety violations. Our attack-detection mechanism has been proven to be sound, meaning that it consistently detects adversarial attacks without any false negatives. In addition, we propose a novel hybrid control law that addresses delays in attack detection and prevents Zeno behavior. We also propose a sampling-based method to verify whether a set is a viability domain for CPS. Finally, we employ a quadratic programming approach for synthesizing control laws for the hybrid control policy, utilizing the viability domain to ensure safety in the presence of adversarial attacks on system actuators. The efficacy of the proposed method is demonstrated in a simulation case study involving a quadrotor system.
Keywords:
Attack detection
control barrier functions (CBF)
nonlinear systems

Journal

IEEE Transactions on Automatic Control cover
IEEE Transactions on Automatic Control
IF:
7
Papers:
1.3W
Citations:
6.7W

Organization

A
arizona state university
Scholars:
3.8K
Papers: 2.0K
Citations: 0
U
University of California
Scholars:
9.7K
Papers: 3.6K
Citations: 8.3W
Cited Papers

Cited Papers

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err2019-10-23
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errBhaskar Ramasubramanian; Luyao Niu; Andrew Clark; Linda Bushnell; Radha Poovendran
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Robust Control Barrier–Value Functions for Safety-Critical Control
err2021-12-14
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errOAAI
errJason J. Choi; Donggun Lee; Koushil Sreenath; Claire J. Tomlin; Sylvia L. Herbert
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