Tag: intrusion detection

A novel SHRSO-K3NN framework achieved 98.8 percent classification accuracy and a 98.4 percent security rate across four standard offline cloud ...

A twelve-month empirical investigation demonstrates that a multi-source intelligence architecture can forecast Black Basta ransomware deployments up to seventy-two hours ...

A new integrated framework combining quantum-inspired optimization and deep learning achieves high accuracy in detecting diverse cyberattacks across major cloud ...

Researchers developed a leakage-aware gated non-local fusion network that groups industrial network-flow records into semantic tokens to enhance multi-class cyberattack ...

Researchers have designed an integrated wireless sensor network framework combining Taylor-series walrus optimization with harmonic neural networks to achieve 92.850 ...

A collaborative edge federated learning model cut threat detection latency and resisted data poisoning across simulated multi-factory test environments.

A systematic review indicates that integrating machine learning detection with automated mitigation improves security and limits operational disruption in industrial ...

A study evaluating XAI on live honeypot telemetry found that tree-based models provide more faithful explanations for intrusion detection than ...

Computer scientists have engineered a dual-branch neural network integrating dynamic channel alignment and temporal gradient gating to classify cybersecurity intrusions ...

A sequential dual-layer edge computing framework integrates soft-voting intrusion detection and gradient boosting to screen clinical network traffic and patient ...