Abstract

Despite the prevalence of markets for malware and exploits and their potential threat to industrial control systems (ICS), existing paradigms for modeling of such cyber-Adversarial behavior do not account for the complex nature of ICS systems consisting of multiple interconnected components. This paper takes the first steps toward addressing this need. Here, we introduce a framework that allows for modeling of ICS systems with highly interconnected components and study this model through the lens of lattice theory. We then turn our attention to the problem of determining the optimal/most dangerous for a cyber-Adversary with respect to this model and find it to be an NP-Complete problem. To address this complexity, we utilize an A∗-based approach and develop admissible heuristics. We provide an implementation and show through a suite of experiments using both simulated and actual vulnerability data that this method performs well in practice for identifying adversarial courses of action in this domain.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data, ISI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages316-318
Number of pages3
ISBN (Electronic)9781509038657
DOIs
StatePublished - Nov 15 2016
Event14th IEEE International Conference on Intelligence and Security Informatics, ISI 2015 - Tucson, United States
Duration: Sep 28 2016Sep 30 2016

Other

Other14th IEEE International Conference on Intelligence and Security Informatics, ISI 2015
CountryUnited States
CityTucson
Period9/28/169/30/16

Keywords

  • Adversarial modeling
  • Cybersecurity

ASJC Scopus subject areas

  • Information Systems
  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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  • Cite this

    Paliath, V., & Shakarian, P. (2016). Modeling cyber-Attacks on industrial control systems. In IEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data, ISI 2016 (pp. 316-318). [7745499] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISI.2016.7745499