Tag: intrusion detection

A benchmark study found that concurrency-aware AI achieved up to 98.9% intrusion-detection accuracy, 2.1-times throughput and 57.5% lower average latency ...

A systematic review of 128 studies finds that secure federated learning in medical IoT requires layered defenses that balance poisoning ...

In a computational evaluation on 5G-NIDD, a deep autoencoder trained only on benign flows and thresholded with an adaptive IQR ...

Researchers at VIT University propose AFI-ID, an intrusion detection framework that unifies adaptive feature selection with attention-based ensemble fusion, achieving ...

A new systematic review of 150 studies argues that AI-driven cybersecurity for the Industrial Internet of Things has reached impressive ...

A graph-augmented framework called IOTTRUST enriches conventional IoT intrusion detection with network flow topology features, achieving 99.07 percent accuracy and ...

Researchers in India have built a hybrid intrusion detection system combining causal learning, entropy-based feature compression, adversarial calibration, and federated ...

A new review argues that as autonomous IoT devices take over critical infrastructure, only adaptive, explainable, and self-healing AI defenses ...

Researchers have developed a semi-supervised, domain-adaptive intrusion detection algorithm that combines mutual-information-maximizing adversarial networks with uncertainty-aware pseudo-labeling to detect attacks ...

A systematic review of 200 studies finds machine learning effective for detecting DDoS and ARP spoofing attacks on university networks, ...