Characterization of a CUSUM model-based sensor attack detector

C.G. Murguia Rendon, Justin Ruths

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

37 Citations (Scopus)

Abstract

In the context of sensor attacks on linear time-invariant cyber-physical systems, we propose a model-based cumulative sum (CUSUM) procedure for identifying falsified sensor measurements. To fulfill a desired detection performance-given the system dynamics, control and estimation schemes, and noise statistics-we derive tools for designing and tuning the CUSUM procedure. We characterize the state degradation that a stealthy attacker can induce to the system while remaining undetected by the detection procedure. Moreover, we quantify the advantage of using a dynamic detector (CUSUM), which leverages the history of the state, over a static detector (Bad-Data) which uses a single measurement at a time. Simulation experiments are presented to illustrate the performance of the detection scheme
Original languageEnglish
Title of host publicationIEEE Conference on Decision and Control
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages7
ISBN (Electronic)978-1-5090-1837-6
DOIs
Publication statusPublished - 29 Dec 2016
Event55th IEEE Conference on Decision and Control (CDC 2016) - Aria Resort and Casino, Las Vegas, United States
Duration: 12 Dec 201614 Dec 2016
Conference number: 55
http://cdc2016.ieeecss.org/

Conference

Conference55th IEEE Conference on Decision and Control (CDC 2016)
Abbreviated titleCDC02016
CountryUnited States
CityLas Vegas
Period12/12/1614/12/16
Internet address

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