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The review synthesizes findings from recent literature to answer four research questions focusing on methodologies in context-based modeling, applications of digital twins and ML in attack detection, and integrating these approaches for improved cyber resilience. The results demonstrate the synergistic potential of combining these technologies, enabling real-time anomaly detection, predictive threat analysis, and adaptive response mechanisms. Challenges such as data limitations, scalability, and verification complexities are vital areas requiring further research. This integrated framework offers a robust pathway for securing critical infrastructure and advancing cybersecurity practices in increasingly interconnected ICS and CPS environments.<\/jats:p>","DOI":"10.1007\/s10207-025-01158-1","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T16:22:24Z","timestamp":1763655744000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards enhanced cybersecurity in industrial control systems: a systematic review of context-based modeling, digital twins, and machine learning approaches"],"prefix":"10.1007","volume":"24","author":[{"given":"Doney","family":"Abraham","sequence":"first","affiliation":[]},{"given":"Gizem","family":"Erceylan","sequence":"additional","affiliation":[]},{"given":"Vasileios","family":"Gkioulos","sequence":"additional","affiliation":[]},{"given":"Siv Hilde","family":"Houmb","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,20]]},"reference":[{"issue":"3","key":"1158_CR1","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/MIE.2019.2962225","volume":"14","author":"S Karnouskos","year":"2020","unstructured":"Karnouskos, S., Leitao, P., Ribeiro, L., Colombo, A.W.: Industrial agents as a key enabler for realizing industrial cyber-physical systems: Multiagent systems entering industry 4.0. 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