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Comparative study of malware detection techniques for industrial control systems.

Reid, Deborah; Harris, Ian; Petrovski, Andrei

Authors

Deborah Reid



Contributors

Naghmeh Moradpoor
Editor

Atilla Elçi
Editor

Abstract

Industrial Control Systems are essential to managing national critical infrastructure, yet the security of these systems historically relies on isolation. The adoption of modern software solutions, and the unique challenges presented by legacy systems, has made securing industrial networks increasingly difficult. With malware identified as the leading cause of cyber incident in industrial systems, this work presents a comparative study of existing malware detection techniques, to compare both accuracy and suitability for use in the defence of industrial systems.

Citation

REID, D., HARRIS, I. and PETROVSKI, A. 2021. Comparative study of malware detection techniques for industrial control systems. In Moradpoor, N., El├ži, A. and Petrovski, A. (eds.) Proceedings of 14th International conference on Security of information and networks 2021 (SIN 2021), 15-17 December 2021, [virtual conference]. Piscataway: IEEE [online], article 19. Available from: https://doi.org/10.1109/SIN54109.2021.9699167

Conference Name 14th International conference on Security of information and networks 2021 (SIN 2021)
Conference Location [virtual conference]
Start Date Dec 15, 2021
End Date Dec 17, 2021
Acceptance Date Dec 7, 2021
Online Publication Date Dec 17, 2021
Publication Date Feb 10, 2022
Deposit Date Feb 11, 2022
Publicly Available Date Feb 11, 2022
Publisher IEEE Institute of Electrical and Electronics Engineers
Book Title Proceedings of the 14th International conference on Security of information and networks 2021 (SIN 2021)
ISBN 9781728192666
DOI https://doi.org/10.1109/SIN54109.2021.9699167
Keywords Industrial control systems; Malware detection; Machine learning; Cybersecurity
Public URL https://rgu-repository.worktribe.com/output/1592334

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