AuthorsY. Wei, S. Zhou, S. Leng, S. Maharjan and Y. Zhang
TitleFederated Learning empowered End-Edge-Cloud Cooperation for 5G HetNet Security
AfilliationCommunication Systems
Project(s)The Center for Resilient Networks and Applications, Simula Metropolitan Center for Digital Engineering
Publication TypeJournal Article
Year of Publication2021
JournalIEEE Network
Date Published03/2021
Publisher IEEE

The distributed and heterogeneous framework in the 5G heterogeneous network (Het-Net) makes it vulnerable to attacks of different kinds. Nodes for improving the network security are therefore important to eliminate such critical threats. Without cooperation or with limited cooperation, these nodes are substantially restricted in their protecting capacity due to specific characteristics such as heterogeneity, hierarchy, and wide range in the 5G HetNet. In this article, we propose a federated learning empowered end-edge-cloud cooperation-based framework for enhancing 5G HetNet security. In this framework, nodes equipped with attack detection mechanisms are distributed in the end, edge, and cloud of the 5G HetNet. We then design cooperative training schemes to realize the full potential of these nodes in detecting attacks. Illustrative results demonstrate the superior performance of our proposed scheme compared to three different benchmark schemes.

Citation Key28071