Researchers at Manipur University have developed EF²RB, an ensemble feature selection framework that boosts IoT intrusion detection accuracy to between...

Researchers have unveiled a data-level prompt injection attack that hijacks graph prompt learning systems by injecting a tiny fraction of...

Researchers at the University of Málaga have built GenPot, a large language model-powered honeypot that fooled cybersecurity experts at chance-level...

Researchers have developed MPAuzz, a greybox fuzzer that uses the nature-inspired Marine Predators Algorithm to intelligently schedule mutations of binary...

Researchers in India have developed BiPC-IFS, a few-shot class-incremental learning framework that lets intrusion detection systems learn new cyberattacks from...

Cybersecurity researchers have unveiled a new artificial intelligence model that dramatically improves how machines identify never-before-seen threat terms buried in...

Cybersecurity researchers have unveiled a new game-theoretic framework that promises to make one of the field's most promising proactive defense...

Researchers at the University of Portsmouth have unveiled V5GIDS, an artificial intelligence-driven intrusion detection framework designed to work natively inside...

Researchers at the Technical University of Košice have shown that even the most impressive-looking scores in machine-learning-based network intrusion detection...

In an era where cyberattacks are often measured solely by downtime, bandwidth and remediation costs, a groundbreaking study from Finland's...