A new fuzzy logic-based trust management scheme called SFFTM distinguishes malicious underwater sensor nodes from honest ones hampered by unstable...

Researchers have combined prototypical few-shot learning with adversarial training to build an IoT intrusion detection system that learns attacks from...

Researchers have built a transformer-based intrusion detection framework that models relationships among network traffic features and outperforms nine baseline AI...

A massive 641-run study shows that trust-weighted federated learning can keep a tiny on-device IoT intrusion detector accurate under non-IID...

As Norway prepares one of its largest-ever security operations for King Harald's funeral, NTNU cybersecurity professor Basel Katt warns that...

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...