Nature-inspired analogies and metaphors for cyber security

Rzeszutko, Elzbieta; Mazurczyk, Wojciech

doi:10.1049/pbse010e_ch1

Cited by 1 publication

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“…However, with securing critical infrastructure, malware detection needs to be optimized and time intelligent as these systems are highly dynamic, complex, and distributed. Nature-inspired metaheuristic algorithms hold the potential to fulfil this much-needed requirement as they can provide effective and fast enough defenses [4]. These algorithms are inspired by the various phenomenon in nature such as ants, dragonfly, bat, firefly, and cuckoo search and are considered useful to solve complex problems without compromising the efficiency of the system being protected [5][6][7].…”

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confidence: 99%

Developing Resilient Cyber-Physical Systems: A Review of State-of-the-Art Malware Detection Approaches, Gaps, and Future Directions

et al. 2023

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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.

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