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Federated learning has emerged as the dominant paradigm for privacy-preserving intrusion detection across distributed networks, yet its vulnerability to adversarial manipulation of the training proces...
Federated learning
Intrusion detection
Non-IID heterogeneity
Byzantine resilience
Adversarial machine learning
Multi-agent systems
Non-stationary distribution attack
