Document Type

Journal Article

Publication Title

Computers

Volume

12

Issue

4

Publisher

MDPI

School

School of Science

RAS ID

54976

Funders

Centre for Muslim States and Societies, School of Social and Cultural Studies, University of Western Australia

Comments

Malik, M. I., Ibrahim, A., Hannay, P., & Sikos, L. F. (2023). Developing resilient cyber-physical systems: A review of state-of-the-art malware detection approaches, gaps, and future directions. Computers, 12(4), 79. https://doi.org/10.3390/computers12040079

Abstract

Cyber-physical systems (CPSes) are rapidly evolving in critical infrastructure (CI) domains such as smart grid, healthcare, the military, and telecommunication. These systems are continually threatened by malicious software (malware) attacks by adversaries due to their improvised tactics and attack methods. A minor configuration change in a CPS through malware has devastating effects, which the world has seen in Stuxnet, BlackEnergy, Industroyer, and Triton. This paper is a comprehensive review of malware analysis practices currently being used and their limitations and efficacy in securing CPSes. Using well-known real-world incidents, we have covered the significant impacts when a CPS is compromised. In particular, we have prepared exhaustive hypothetical scenarios to discuss the implications of false positives on CPSes. To improve the security of critical systems, we believe that nature-inspired metaheuristic algorithms can effectively counter the overwhelming malware threats geared toward CPSes. However, our detailed review shows that these algorithms have not been adapted to their full potential to counter malicious software. Finally, the gaps identified through this research have led us to propose future research directions using nature-inspired algorithms that would help in bringing optimization by reducing false positives, thereby increasing the security of such systems.

DOI

10.3390/computers12040079

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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