Temporal Authentication Model for The Internet of Things Edge Devices for Sustainable User Privacy

Internet of Things (IoT) integrated edge devices are used in different real-time applications for providing cloud-based services to the users. ‎As security issues are open in such integrated device platforms, the need for device authentication and user privacy is mandatory. This article, therefore, introduces a Temporal Authentication Model (TAM) for IoT-edge devices to sustain user privacy demands. The proposed ‎model employs distributed federated learning to validate authentication and revocation processes under different sharing intervals. A temporal factor is used to validate the authentication sustainability without key changes across the sharing intervals. This temporal factor is used ‎to decide the authentication or revocation for different devices. The distributed federated learning verifies the balance between these two ‎processes to ensure maximum authentication. Thus, the proposed TAM improves the authentication rate by 11.39% and reduces the revocation failure by 11.39%, authentication time by 12.44%, and complexity by 11.61% for the operation time.