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InfoResearchPeer-reviewed
Robust multi-class DDoS and fraud detection using a Context-Adaptive Deep Evolutionary Game Framework with CNN–BiGRU
- Published
- Record updated
Summary
Researchers propose a hybrid deep learning framework combining CNN and BiGRU to detect DDoS and other network attacks in real time. Their Neuro-Evolutionary Resampling Algorithm (NERA) addresses class imbalance, and the Context-Adaptive Deep Evolutionary Game Framework (CADEGF) aims to improve resistance to adversarial attacks. The study reports high classification accuracy and effective detection of minority classes, while noting trade-offs between minority-class detection and adversarial robustness.