- Title
- Statistical approach to detection of attacks for stochastic cyber-physical systems
- Creator
- Marelli, Damián; Sui, Tianju; Fu, Minyue
- Relation
- 2nd IFAC Workshop on Linear Parameter Varying Systems (LPVS) / 9th IFAC Symposium on Robust Control Design (ROCOND). 2nd IFAC Workshop on Linear Parameter Varying Systems (LPVS) / 9th IFAC Symposium on Robust Control Design (ROCOND):Proceedings [presented in IFAC-PapersOnLine, Vol. 51, No. 25] (Florianopolis, Brazil 03-05 September, 2018) p. 178-183
- Publisher Link
- http://dx.doi.org/10.1016/j.ifacol.2018.11.101
- Publisher
- Elsevier
- Resource Type
- conference paper
- Date
- 2018
- Description
- We study the problem of detecting an attack on a stochastic cyber-physical system. We start by proposing a detection criterion based on checking the statistics of the Kalman prediction error. To show the importance of the proposed criterion, we study certain attacking schemes which can be effectively detected by this criterion, but not by checking simpler conditions based on commonly used statistics. We then use the proposed criterion to derive a detection algorithm. This algorithm is based on a statistical confidence test, giving a confidence level for detecting an attack. We present simulation results to illustrate the performance of this algorithm.
- Subject
- system security; linear systems; cyber-physical systems; integrity attacks; attack detection; statistical hypothesis testing
- Identifier
- http://hdl.handle.net/1959.13/1405398
- Identifier
- uon:35483
- Identifier
- ISSN:2405-8963
- Language
- eng
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