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

• Published in: Computers (Basel) Vol. 12; no. 4; p. 79
• Main Authors: Malik, M. Imran, Ibrahim, Ahmed, Hannay, Peter, Sikos, Leslie F.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-04-2023
• Subjects: Algorithms; Artificial intelligence; Communication; Communications networks; Computer crimes; Computers; critical infrastructures; Cyber-physical systems; Cybersecurity; Data security; Denial of service attacks; Energy industry; Heuristic methods; Human-machine systems; Information technology; Infrastructure; Internet; Malware; Medical device industry; Medical equipment; metaheuristics; Methods; National security; nature-inspired algorithms; Nuclear power plants; Optimization; Personal computers; Prevention; Public health; Safety and security measures; Security management; Smart cities; Smart grid; Smartphones; Software; Spyware; State-of-the-art reviews; System effectiveness; Australia; United States > US
• ISSN: 2073-431X; 2073-431X
• DOI: 10.3390/computers12040079

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.