Tag: network security

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

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 ...

Researchers have developed ZD-HybridNet, a hybrid Transformer-LSTM deep learning framework that detects attack categories withheld from training and explains its ...

Researchers have developed a hybrid Grey Wolf Coot Optimization routing framework with dynamic physically unclonable functions that cuts IoT energy ...

Researchers in India report that a Bayesian-optimized decision tree detects black hole attacks in RPL-based IoT networks with 98.71% accuracy, ...

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

A new systematic review in Artificial Intelligence Review maps how multi-objective optimization algorithms are being used to balance accuracy, false ...

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

Researchers in Vietnam have developed a Dual SPLIR epidemic-style model that incorporates APT dormancy, network heterogeneity, and organizational policy to ...