Lightweight Authentication in Edge Collaborations Utilizing Multi-dimensional Historical Information: Design and Implementation

While edge collaborations play more and more important roles in the sixth-generation (6G) network, the authentication among devices for trusted collaborations is more challenging. The existing authentication mechanisms may suffer from the long latency and high computation overhead in such application scenarios, especially when the collaboration group is large. In this paper, a lightweight group authentication scheme based on multi-dimensional historical information is proposed and implemented in a specific federated learning-based collaborative outdoor localization scenario. To further illustrate, the multi-dimensional historical information consists of the learning parameters and environment sensing data collected by lidar from the latest round of collaboration. Then, we design a key generation strategy based on the historical information and develop a group authentication protocol. In the proposed scheme, every device in the group can identify the others at once based on their broadcasting keys, which will be renewed automatically before every round of collaboration. Hence, the proposed scheme achieves lightweight group authentication and high security. Both implementation and simulation results demonstrate the validity and superior performance of the proposed scheme compared with the existing schemes.