Sound and Complete State Estimation for Linear Dynamical Systems Under Sensor Attacks Using Satisfiability Modulo Theory Solving
Yasser Shoukry, Alberto Puggelli, Pierluigi Nuzzo, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia, and Paulo Tabuada. Sound and Complete State Estimation for Linear Dynamical Systems Under Sensor Attacks Using Satisfiability Modulo Theory Solving. In Proceedings of the American Control Conference (ACC 2015), pp. 3818–3823, July 2015.
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Abstract
We address the problem of detecting and mitigating the effect of malicious attacks on the sensors of a linear dynamical system. We develop a novel, efficient algorithm that uses a Satisfiability Modulo Theory approach to isolate the compromised sensors and estimate the system state despite the presence of the attack, thus harnessing the intrinsic combinatorial complexity of the problem. Simulation results show that our algorithm compares favorably with alternative techniques, with respect to both runtime and estimation error.
BibTeX
@inproceedings{shoukry-acc15, author = {Yasser Shoukry and Alberto Puggelli and Pierluigi Nuzzo and Alberto L. Sangiovanni-Vincentelli and Sanjit A. Seshia and Paulo Tabuada}, title = {Sound and Complete State Estimation for Linear Dynamical Systems Under Sensor Attacks Using Satisfiability Modulo Theory Solving}, booktitle = {Proceedings of the American Control Conference (ACC 2015)}, month = "July", year = {2015}, pages = "3818--3823", abstract = {We address the problem of detecting and mitigating the effect of malicious attacks on the sensors of a linear dynamical system. We develop a novel, efficient algorithm that uses a Satisfiability Modulo Theory approach to isolate the compromised sensors and estimate the system state despite the presence of the attack, thus harnessing the intrinsic combinatorial complexity of the problem. Simulation results show that our algorithm compares favorably with alternative techniques, with respect to both runtime and estimation error.}, }