A Novel Federated Learning Method to Model Cybersecurity Risk Estimation for Digital Identity Management Systems

A Novel Federated Learning Method to Model Cybersecurity Risk Estimation for Digital Identity Management Systems

Explore a novel federated learning method for modeling cybersecurity risk estimation in digital identity management systems. In this 22-minute conference talk, Po-Chu Chen from the University of Warwick presents research conducted at the Alan Turing Institute. Gain insights into the socio-technical infrastructure opportunities and challenges surrounding the implementation of trustworthy digital identity systems within countries. Discover how this innovative approach can enhance cybersecurity risk assessment for digital identity management, bridging the gap between academic research and practical applications in government and industry sectors.