Fedzora: A Privacy-Preserving Federated Learning Framework for Cybersecurity AI

Abstract: Fedzora is a federated learning framework designed to enable collaborative training of AI models for cybersecurity applications while preserving data privacy. The framework integrates secure aggregation, differential privacy, and model validation to allow organizations to train threat-detection models without exposing raw sensitive data. This paper briefly presents Fedzora’s architecture, methodology, and deployment considerations.

Keywords: Cybersecurity, AI, ML, Fedzora Project, Vulnerability Assessment, Ethical Hacking, Quantum-Resistant Cryptography.