Neurosymbolic models for ensuring cybersecurity in critical cyberphysical systems

S.O. Yevdokymov

Abstract


The article presents the results of a comprehensive study on the application of the neuro-symbolic approach for detecting and preventing cyber threats in railway systems, a critical component of cyber-physical infrastructure. The increasing complexity and integration of physical systems with digital technologies have made such infrastructure vulnerable to cyberattacks, where disruptions can lead to severe consequences, including system failures, financial losses, and threats to public safety and the environment.

Prombles in programming 2025; 1: 63-73


Keywords


neurosymbolic approach; cyber-physical systems; machine learning; cyber security; critical infrastructure

References


Taylor, Alex. "Neuro-Symbolic Methods for Cyber Secu-rity". Journal of Artificial Intelligence Research, vol. 12, no. 3, 2021, pp. 500-515.

Alashkar H., Ahmad M. A Comprehensive Review on Machine Learning Techniques for Cyber-Physical Sys-tems. Journal of Systems Architecture, 2023, Vol. 129, pp. 102649. DOI: 10.1016/j.sysarc.2022.102649

Mishra A., Gupta R. An Overview of Cyber Physical Systems: Applications, Challenges, and Future Direc-tions. ACM Computing Surveys, 2022, Vol. 55, № 9, pp. 1–35. DOI: 10.1145/3498707

Vural C., Akbulut U. Cyber-Physical Systems Security: Threats and Machine Learning Countermeasures. IEEE Transactions on Emerging Topics in Computing, 2023, Vol. 11, № 2, pp. 417–426. 10.1109/TETC.2023.3238515

Garfinkel, S., Adams, C., & Warfield, J. (2014). Under-standing cyber-physical attacks and defenses. IEEE Secu-rity & Privacy, 12(1), 20-26.

Zhang, Wei, et al. "Adaptive Security Models for Cyber-Physical Systems". In Trends in Cyber-Physical Systems Security, edited by Laura Brown, vol. 5, Cham: Springer, 2022, pp. 200-215.

White, Sarah, et al. "Challenges in Protecting Railway Infrastructure". Transport Security Journal, vol. 6, no. 4, 2020, pp. 210-225.

Yevdokymov S. O. Modern systems of information pro-tection Oleksandrovich / Serhiy Yevdokymov. - Kyiv: Drukaryk, 2023. - 380 p.

Yevdokymov S. O. Applied systems for choosing the optimal route in transport / Serhiy Oleksandrovich Yevdokimov. - Kyiv: FOP Gulyaeva V.M., 2024. - 200 p.

Parker, Sam. "The Role of Cryptography in Securing Cyber-Physical Systems". In Cyber Security: Principles and Practices, edited by Alan Richards, New York: Wiley, 2021, pp. 130-150.

Khan M. A., Ali S. Machine Learning for Cybersecurity in Cyber-Physical Systems: Recent Advances and Future Directions. Journal of Network and Computer Applications, 2023, Vol. 209, pp. 103531. DOI: 10.1016/j.jnca.2023.103531

Sahu A., Dutta S. Emerging Trends in Cyber Physical Systems Security: A Review of Machine Learning Solu-tions. Computers & Security, 2022, Vol. 114, pp. 103701. DOI: 10.1016/j.cose.2022.103701

Kumar R., Tripathi A. Anomaly Detection in Cyber-Physical Systems Using Ensemble Learning Techniques. IEEE Transactions on Industrial Informatics, 2023, Vol. 19, № 2, pp. 1253–1263. DOI: 10.1109/TII.2023.3242145

Green, Laura, et al. "Real-Time Threat Detection in Cyber-Physical Systems". Journal of Cyber Security, vol. 15, no. 2, 2021, pp. 200-210.

Zhang H., Xu J. Neural-Symbolic Approaches for Cyber-Physical Systems: Enhancing Anomaly Detection. Artifi-cial Intelligence Review, 2023, Vol. 56, № 1, pp. 321–347. DOI: 10.1007/s10462-022-10256-8

Katz, G., et al. "Combining Neural Networks and Symbolic Reasoning for Enhanced Security in Cyber-Physical Systems." Proceedings of the International Conference on Neural Information Processing Systems (NeurIPS), 2023, pp. 234-246.

Yevdokymov S. O. System programming: Creating appli-cations on Assembler / Serhiy Oleksandrovich Yevdokimov. – 2nd ed., supplemented and revised. - London, United Kingdom: LAP LAMBERT Academic Publishing, 2024. - 133 p.

Johnson, Mark. "Ensuring Data Integrity and Confidenti-ality in Cyber-Physical Systems". International Journal of Cyber Security, vol. 8, no. 3, 2022, pp. 300-315.

Rahman M. M., Saha A. Anomaly Detection in Cyber-Physical Systems: A Hybrid Approach. Future Genera-tion Computer Systems, 2022, Vol. 128, pp. 132–146. DOI: 10.1016/j.future.2021.12.035


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