SMTBased Observer Design for CyberPhysical Systems under Sensor Attacks
(2016) 7th ACM/IEEE International Conference on CyberPhysical Systems, ICCPS 2016 Abstract
We introduce a scalable observer architecture to estimate the states of a discretetime lineartimeinvariant (LTI) system whose sensors can be manipulated by an attacker. Given the maximum number of attacked sensors, we build on previous results on necessary and sufficient conditions for state estimation, and propose a novel multimodal Luenberger (MML) observer based on efficient Satisfiability Modulo Theory (SMT) solving. We present two techniques to reduce the complexity of the estimation problem. As a first strategy, instead of a bank of distinct observers, we use a family of filters sharing a single dynamical equation for the states, but different output equations, to generate estimates corresponding to different subsets of... (More)
We introduce a scalable observer architecture to estimate the states of a discretetime lineartimeinvariant (LTI) system whose sensors can be manipulated by an attacker. Given the maximum number of attacked sensors, we build on previous results on necessary and sufficient conditions for state estimation, and propose a novel multimodal Luenberger (MML) observer based on efficient Satisfiability Modulo Theory (SMT) solving. We present two techniques to reduce the complexity of the estimation problem. As a first strategy, instead of a bank of distinct observers, we use a family of filters sharing a single dynamical equation for the states, but different output equations, to generate estimates corresponding to different subsets of sensors. Such an architecture can reduce the memory usage of the observer from an exponential to a linear function of the number of sensors. We then develop an efficient SMTbased decision procedure that is able to reason about the estimates of the MML observer to detect at runtime which sets of sensors are attackfree, and use them to obtain a correct state estimate. We provide proofs of convergence for our algorithm and report simulation results to compare its runtime performance with alternative techniques. Our algorithm scales well for large systems (including up to 5000 sensors) for which many previously proposed algorithms are not implementable due to excessive memory and time requirements. Finally, we illustrate the effectiveness of our algorithm on the design of resilient power distribution systems.
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 author
 Shoukry, Yasser; Chong, Michelle ^{LU} ; Wakaiki, Masashi; Nuzzo, Pierluigi; SangiovanniVincentelli, Alberto L.; Seshia, Sanjit A.; Hespanha, João P. and Tabuada, Paulo
 organization
 publishing date
 20160525
 type
 Chapter in Book/Report/Conference proceeding
 publication status
 published
 subject
 host publication
 2016 ACM/IEEE 7th International Conference on CyberPhysical Systems, ICCPS 2016  Proceedings
 publisher
 Institute of Electrical and Electronics Engineers Inc.
 conference name
 7th ACM/IEEE International Conference on CyberPhysical Systems, ICCPS 2016
 conference location
 Vienna, Austria
 conference dates
 20160411  20160414
 external identifiers

 scopus:84979084449
 ISBN
 9781509017720
 DOI
 10.1109/ICCPS.2016.7479119
 language
 English
 LU publication?
 yes
 id
 d8199bc86f0a4a629da9e453b5781203
 date added to LUP
 20170127 11:34:32
 date last changed
 20190106 12:54:05
@inproceedings{d8199bc86f0a4a629da9e453b5781203, abstract = {<p>We introduce a scalable observer architecture to estimate the states of a discretetime lineartimeinvariant (LTI) system whose sensors can be manipulated by an attacker. Given the maximum number of attacked sensors, we build on previous results on necessary and sufficient conditions for state estimation, and propose a novel multimodal Luenberger (MML) observer based on efficient Satisfiability Modulo Theory (SMT) solving. We present two techniques to reduce the complexity of the estimation problem. As a first strategy, instead of a bank of distinct observers, we use a family of filters sharing a single dynamical equation for the states, but different output equations, to generate estimates corresponding to different subsets of sensors. Such an architecture can reduce the memory usage of the observer from an exponential to a linear function of the number of sensors. We then develop an efficient SMTbased decision procedure that is able to reason about the estimates of the MML observer to detect at runtime which sets of sensors are attackfree, and use them to obtain a correct state estimate. We provide proofs of convergence for our algorithm and report simulation results to compare its runtime performance with alternative techniques. Our algorithm scales well for large systems (including up to 5000 sensors) for which many previously proposed algorithms are not implementable due to excessive memory and time requirements. Finally, we illustrate the effectiveness of our algorithm on the design of resilient power distribution systems.</p>}, author = {Shoukry, Yasser and Chong, Michelle and Wakaiki, Masashi and Nuzzo, Pierluigi and SangiovanniVincentelli, Alberto L. and Seshia, Sanjit A. and Hespanha, João P. and Tabuada, Paulo}, isbn = {9781509017720}, language = {eng}, location = {Vienna, Austria}, month = {05}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, title = {SMTBased Observer Design for CyberPhysical Systems under Sensor Attacks}, url = {http://dx.doi.org/10.1109/ICCPS.2016.7479119}, year = {2016}, }