Cybersecurity in SCADA Systems with Advanced AI and ML Techniques
2024 IEEE 65th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2024): Proceedings 2024
Heinrihs Kristians Skrodelis, Rudolfs Kelle, Andrejs Romānovs

SCADA systems are crucial for monitoring and controlling key infrastructures such as power grids, water supply, transportation networks, and industrial processes. With the increasing interconnectivity and complexity of these systems, they are exposed to numerous cybersecurity challenges. This paper provides a comprehensive literature review focusing on the vulnerabilities in SCADA systems and explores measures to mitigate these risks. Key vulnerabilities include the lack of built-in security mechanisms, open access networks, proprietary protocols, reliance on legacy systems and insecure network architectures. Various cybersecurity strategies such as adopting security standards, utilizing encryption, regular updates, network segmentation, intrusion detection systems (IDS) and security information and event management (SIEM) are discussed to enhance SCADA security. Additionally, the paper highlights the growing significance of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing the security and robustness of SCADA systems.


Atslēgas vārdi
SCADA , Cybersecurity , Industrial Control Systems , Operational Technology , Artificial Intelligence , Machine Learning
DOI
10.1109/ITMS64072.2024.10741936
Hipersaite
https://ieeexplore-ieee-org.resursi.rtu.lv/document/10741936

Skrodelis, H., Kelle, R., Romānovs, A. Cybersecurity in SCADA Systems with Advanced AI and ML Techniques. No: 2024 IEEE 65th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2024): Proceedings, Latvija, Riga, 3.-4. oktobris, 2024. Piscataway: IEEE, 2024, 118.-122.lpp. ISBN 979-8-3315-3384-7. e-ISBN 979-8-3315-3383-0. ISSN 2771-6953. e-ISSN 2771-6937. Pieejams: doi:10.1109/ITMS64072.2024.10741936

Publikācijas valoda
English (en)
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