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Scalable Cyber-physical Optimal Response Engine

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Industry Partnership Demonstrates ML-Based Classification for Secure Network Rules

Posted on January 29, 2025 by manveer488

Cooperative work with Vistra continues to refine machine learning models that classify and interpret firewall rules for power grid operations. Sample firewall data was analyzed with Random Forest and AdaBoost algorithms, reaching accuracy rates between 88% and 99%. Additional refinements aim to expand model generalization, improve policy recommendations, and enhance proactive risk-based mitigation in operational environments.

Filed Under: News

SCORE is funded by the U.S. Department of Energy (DOE) under award DE-CR0000018.
The Federal Project Officers for this project are Robert Hayes and Prima Assante. 

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