A Novel Centrality-Driven Machine Learning Approach for Clustering Critical Nodes in Cyber-Physical Power Systems

Mehdi Doostinia, Davide Falabretti, Giacomo Verticale and Sadegh Bolouki

Article (2026)

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Department:	Department of Computer Engineering and Software Engineering
PolyPublie URL:	https://publications.polymtl.ca/75300/
Journal Title:	IEEE Transactions on Industry Applications
Publisher:	Institute of Electrical and Electronics Engineers
DOI:	10.1109/tia.2026.3675071
Official URL:	https://doi.org/10.1109/tia.2026.3675071
Date Deposited:	01 Apr 2026 16:35
Last Modified:	02 Apr 2026 11:14

Cite in APA 7:	Doostinia, M., Falabretti, D., Verticale, G., & Bolouki, S. (2026). A Novel Centrality-Driven Machine Learning Approach for Clustering Critical Nodes in Cyber-Physical Power Systems. IEEE Transactions on Industry Applications, 1-12. https://doi.org/10.1109/tia.2026.3675071
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