Scalable Industrial Control System Analysis via XAI-Based Gray-Box Fuzzing

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

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Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings - 2023 38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Pages1803-1807
ISBN (electronic)979-8-3503-2996-4
ISBN (print)979-8-3503-2997-1
Publication statusPublished - 2023

Publication series

NameProceedings - IEEE/ACM International Conference on Automated Software Engineering, ASE
ISSN (Print)1938-4300
ISSN (electronic)2643-1572

Conference

Title38th IEEE/ACM International Conference on Automated Software Engineering (ASE 2023)
LocationEuropean Convention Center Luxembourg (ECCL)
PlaceLuxembourg
CityEchternach
Period11 - 15 September 2023

Abstract

Conventional approaches to analyzing industrial control systems have relied on either white-box analysis or black-box fuzzing. However, white-box methods rely on sophisticated domain expertise, while black-box methods suffers from state explosion and thus scales poorly when analyzing real ICS involving a large number of sensors and actuators. To address these limitations, we propose XAI-based gray-box fuzzing, a novel approach that leverages explainable AI and machine learning modeling of ICS to accurately identify a small set of actuators critical to ICS safety, which result in significant reduction of state space without relying on domain expertise. Experiment results show that our method accurately explains the ICS model and significantly speeds-up fuzzing by 64x when compared to conventional black-box methods. © 2023 IEEE.

Research Area(s)

  • Explainable AI, Fuzzing, Industrial Control Systems, Learning based Approaches, Security Attack

Bibliographic Note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Citation Format(s)

Scalable Industrial Control System Analysis via XAI-Based Gray-Box Fuzzing. / Kur, Justin; Chen, Jingshu; Huang, Jun.
Proceedings - 2023 38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023. Institute of Electrical and Electronics Engineers, Inc., 2023. p. 1803-1807 (Proceedings - IEEE/ACM International Conference on Automated Software Engineering, ASE).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review