Several methods have been proposed by researchers to detect cyber attacks in Cyber–Physical Systems (CPSs). This paper proposes a comprehensive approach for conducting experiments to assess the effectiveness of such methods in the context of a robot (Amigobot) that includes both cyber and physical components. The proposed approach includes a method for performing vulnerability analysis, several methods for attack detection, and guidelines for conducting experimental studies in the context of cyber security. The method for vulnerability analysis makes use of the Failure-Attack-CounTermeasure (FACT) graph. The experimental study to evaluate methods for attack detection comprises of three experiments. These methods have been implemented and evaluated, within and across all three experiments, with respect to their effectiveness, detection speed, and durability for injection, scaling, and stealthy attacks. The proposed guidelines define key phases and artifacts for conducting such experiments and are an adaptation of those used in Software Engineering.
Bibliographical noteNOTICE: this is the author’s version of a work that was accepted for publication in Robotics and Autonomous Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Robotics and Autonomous Systems, 98, (2017)
© 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
- Cyber–physical systems
- CUSUM method
- Intelligent checker
- FACT graph