Researchers have built a federated, explainable VAE-LSTM framework that detects previously unseen DDoS attacks in software-defined healthcare networks with over...

Researchers have unveiled a federated learning framework that detects DDoS attacks across IoT networks with up to 96.95 percent accuracy...

A new cross-domain handover framework for vehicular networks combines one-time anonymous credentials with graph-attention and federated anomaly detection, achieving strong...

Florida Atlantic University has received a $200,000 NIST cooperative agreement, in partnership with D-Wave Quantum, to build a regional quantum...

A new study shows that adaptively fusing a closed-world classifier with an unsupervised open-set detector significantly improves detection of zero-day...

Researchers have built ChatTracer, a lightweight intrusion detection framework that fine-tunes a compact large language model to classify wireless sensor...

A new conceptual study argues that AI-generated cybersecurity outputs only become useful when embedded in formal decision structures that validate,...

Researchers in Vietnam show that multimodal intrusion detection systems hardened with adversarial training can resist transferable adversarial examples generated by...

An open-source simulation framework called DDoSimu5G generates precisely labeled DDoS attack datasets inside a simulated 5G network, giving machine-learning intrusion...

Researchers in China have developed a detection method that combines temporal knowledge graphs, time-series tensors, and a variational autoencoder paired...