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November 4, 2025

Federated Learning for Enhancing Cybersecurity Resilience in Distributed Energy Systems

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Authors

VMV. MishraLovely Professional University

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Implication

Research shows improved anomaly detection accuracy in energy systems using federated learning, suggesting enhanced threat response.

Key Points

  • Federated learning approach improved anomaly detection accuracy significantly in distributed energy systems, demonstrating robust capabilities.
  • The system achieved a high threat detection rate with zero false positives, after conducting seven training rounds of model updates.
  • Federated Learning architecture operated across a network of over 20 geographically distributed nodes without sharing raw operational data.
  • This privacy-preserving solution addresses significant cybersecurity challenges while ensuring compliance with energy regulatory standards.

Cite This Study

V. Mishra (2025) studied this question.

synapsesocial.com/papers/6909452d8f2297dc13532bbchttps://doi.org/10.2118/229330-ms
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