AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Intrusion Detection Systems (IDS) deployed in modern networks face persistent challenges arising from severe class imbalance, latent temporal dependencies in traffic behavior, and the limitations of purely discriminative learning models. Existing deep learning-based IDS approaches typically address these issues indepen...
Federated Learning (FL) enables distributed training while keeping data local, but exchanged model updates can leak information through membership inference attacks. Differential privacy mitigates this risk via noise injection; however, aggressive DP regimes with strong noise can destabilize large models. An SNR-guided...
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