Monitoring Cyber-Physical Systems Using a Tiny Twin to Prevent Cyber-AttacksShow others and affiliations
2022 (English)In: Lecture Notes in Computer Science, vol. 13255, Springer Science and Business Media Deutschland GmbH , 2022, p. 24-43Conference paper, Published paper (Refereed)
Abstract [en]
We propose a method to detect attacks on sensors and controllers in cyber-physical systems. We develop a monitor that uses an abstract digital twin, Tiny Twin, to detect false sensor data and faulty control commands. The Tiny Twin is a state transition system that represents the observable behavior of the system from the monitor point of view. At runtime, the monitor observes the sensor data and the control commands, and checks whether the observed data and commands are consistent with the state transitions in the Tiny Twin. The monitor produces an alarm when an inconsistency is detected. We model the components of the system and the physical processes in the Rebeca modeling language and use its model checker to generate the state space. The Tiny Twin is built automatically by reducing the state space, keeping the observable behavior of the system, and preserving the trace equivalence. We demonstrate the method and evaluate it in detecting attacks using a temperature control system.
Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH , 2022. p. 24-43
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 13255 LNCS
Keywords [en]
Abstraction, Attack detection and prevention, Cyber-physical systems, Cyber-security, Model checking, Monitoring, Cyber Physical System, Cybersecurity, Embedded systems, Modeling languages, Network security, Attack detection, Attack prevention, Control command, Cybe-physical systems, Cyber security, Models checking, Observable behavior, Sensors data
National Category
Robotics
Identifiers
URN: urn:nbn:se:mdh:diva-59941DOI: 10.1007/978-3-031-15077-7_2ISI: 000874749700002Scopus ID: 2-s2.0-85137039734ISBN: 9783031150760 (print)OAI: oai:DiVA.org:mdh-59941DiVA, id: diva2:1695591
Conference
28th International Symposium on Model Checking Software, SPIN 2022, Virtual, Online, 21 May, 2022
2022-09-142022-09-142024-04-14Bibliographically approved
In thesis