Tag: anomaly detection

A Paillier-CKKS framework encrypted federated-learning updates and reached 94.67% average accuracy on Medical-MNIST during simulated reverse-engineering attacks.

A compact hybrid Transformer-graph attention autoencoder reconstructs downhole geomechanical states from unlabelled drilling data, outperforming standalone models and surviving simulated ...

Researchers have built a three-layer AI framework for 5G mobile learning that cuts device energy use by up to 27 ...

Researchers in India built a transformer-based deep learning system to detect anomalies in solar-wind power plants, achieving strong reconstruction accuracy ...

Researchers at the University of Tübingen and Carl Zeiss Vision have built a real-time AI system that detects anomalous gaze ...

Researchers at Vellore Institute of Technology have developed TOAD-ML, a machine learning framework that validates decentralized finance oracle price feeds ...

Smart grids promise a cleaner, more responsive electricity system, but they also carry a hidden vulnerability: every smart meter is ...

Machine learning and SHAP explainability reveal conditional disclosure-stability patterns across seven Palestinian banks, offering supervisors an early-warning triage tool.

A new framework fuses an unsupervised machine learning ensemble with a lightweight blockchain to detect and confirm intrusions in wireless ...

A new autonomous AI framework called DriftGuard detects, diagnoses, and corrects calibration drift in ocean sensor networks up to three ...