Researchers have developed a 117-practice readiness index, validated by an expert panel and a case study, to assess cybersecurity preparedness...

A new open-access review proposes a four-component framework combining compliance floors, loss-based benchmarks, real options staging and FERC incentives to...

A new framework called TinyRoute combines TinyML, reinforcement learning, and few-shot learning to achieve adaptive routing and zero-day attack detection...

A mixed-method study combining a bibliometric review of 2,015 publications with interviews of 10 developers and 10 users finds that...

A study combining Transformer, deep neural-network and recurrent models with adaptive weighting reported 95% accuracy and 96% recall when detecting...

A fuzzy autoencoder classified none of 10,000 adversarially generated executable samples as legitimate and reached a reported safety-aware accuracy of...

A new review argues that cybersecurity should be understood as a social-physical phenomenon in which resilience and vulnerability emerge from...

Researchers have introduced CAE-IDS, an intrusion detection framework that pairs a Concrete Autoencoder-based feature selection mechanism with Bayesian hyperparameter optimization,...

A deployment-efficient CNN-LSTM framework with channel attention detects encrypted, imbalanced, and heterogeneous malicious traffic in real time on CPU-only hardware,...

A new framework combines TPE-optimized stacking of gradient boosting models with differential privacy and a SHAP-based compliance audit, achieving 99.21...