Tag: intrusion detection

Researchers have developed a feedback-guided framework that adapts decision thresholds instead of retraining classifiers, achieving near-equal accuracy with lower false ...

A new federated learning framework called FedCAMP-IDS detects known and zero-day cyberattacks across heterogeneous IoT networks with up to 99.16 ...

A new blockchain-enabled federated learning framework called IoV BCFL+ detects intrusions across connected vehicle networks with over 96 percent accuracy ...

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

Researchers have developed an order-preserving framework based on intuitionistic fuzzy soft sets, order-isomorphism, and topological sorting that improves the accuracy ...

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

Researchers in Beijing have built a 0.27-megabyte transformer model that detects multi-stage APT attacks in industrial IoT telemetry with high ...

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

A Nature Food Perspective drawing on a workshop series of more than 150 stakeholders proposes a land-grant university-led Agricultural Cybersecurity ...

Researchers have developed an immune cooperative hybrid breeding optimization algorithm that selects features more effectively for intrusion detection, outperforming 13 ...