H. Dinh

Investigating Contrastive Learning for Conditional Variational Autoencoders in Network Intrusion Detection

Class imbalance, where majority-class samples vastly outnumber minority-class samples, remains a persistent challenge in network intrusion detection systems (NIDS), often causing classifiers to overlook rare but critical attack types while yielding misleadingly optimistic performance metrics. Synthetic data generation...