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Author: Rapolas Kateiva
Hariprasad Sivaraman, USA Introduction: A New Era of Collaboration and Security In an increasingly interconnected world, the sharing of threat intelligence is critical for U.S. agencies to counter sophisticated cyberattacks. However, traditional approaches to threat intelligence sharing face significant challenges, including privacy concerns, data sensitivity, and compliance with strict regulations. Federated learning, an emerging machine learning paradigm, offers a groundbreaking solution by enabling agencies to collaboratively train models on decentralized data while preserving its privacy. This technology holds immense potential for strengthening cybersecurity across federal systems without compromising sensitive information. What Is Federated Learning? Federated learning is a distributed machine…