2 papers
cs.CR2026
Towards Securing IIoT: An Innovative Privacy-Preserving Anomaly Detector Based on Federated Learning
Samira Kamali Poorazad, Chafika Benzaïd, Tarik Taleb
In the light of the growing connectivity and sensitivity of industrial data, cyberattacks and data breaches are becoming more common in the Industrial Internet of Things (IIoT). To…
cs.CR2024
A Novel Buffered Federated Learning Framework for Privacy-Driven Anomaly Detection in IIoT
Samira Kamali Poorazad, Chafika Benzaid, Tarik Taleb
Industrial Internet of Things (IIoT) is highly sensitive to data privacy and cybersecurity threats. Federated Learning (FL) has emerged as a solution for preserving privacy, enabli…