Comparison of corrupted sensor data detection methods in detecting stealthy attacks on cyber-physical systems

G. Sabaliauskaite, G.S. Ng, J. Ruths, A. Mathur

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

1 Citation (Scopus)

Abstract

Effectiveness of seven methods for detecting stealthy attacks on Cyber Physical Systems (CPS) was investigated using an experimental study. The Amigobot robot was used as the CPS. The experiments were conducted in simulation as well as on the physical robot. Three types of stealthy attacks were implemented: surge, bias, and geometric. Two variations of Cumulative Sum (CUSUM) method for detecting attacks were evaluated: partial and full physics. Four attack scenarios were implemented. Results from the experiments indicate that stealthy attacks could remain undetected by the CUSUM methods for some attack scenarios. In addition to the CUSUM-based methods, a set of five methods to complement CUSUM were implemented and their effectiveness assessed. While the additional methods do improve the effectiveness of CUSUM-based methods, some attacks remained undetected regardless of which method, or a combination of methods, was used for detection due to the amount of variation in sensor measurements between different runs in simulation and in the physical robot.
Original languageEnglish
Title of host publication 2017 IEEE 22nd Pacific Rim International Symposium on Dependable Computing (PRDC)
PublisherIEEE
ISBN (Electronic)978-1-5090-5652-1
ISBN (Print)978-1-5090-5653-8
DOIs
Publication statusPublished - 8 May 2017
Externally publishedYes
Event22nd Pacific Rim International Symposium on Dependable Computing (PRDC) - Christchurch, New Zealand
Duration: 22 Jan 201725 Jan 2017

Conference

Conference22nd Pacific Rim International Symposium on Dependable Computing (PRDC)
Abbreviated titlePRDC2017
CountryNew Zealand
CityChristchurch
Period22/01/1725/01/17

Fingerprint Dive into the research topics of 'Comparison of corrupted sensor data detection methods in detecting stealthy attacks on cyber-physical systems'. Together they form a unique fingerprint.

  • Cite this

    Sabaliauskaite, G., Ng, G. S., Ruths, J., & Mathur, A. (2017). Comparison of corrupted sensor data detection methods in detecting stealthy attacks on cyber-physical systems. In 2017 IEEE 22nd Pacific Rim International Symposium on Dependable Computing (PRDC) IEEE. https://doi.org/10.1109/PRDC.2017.47