Federated Lightweight Transformer for Network-Layer Cyberattack Detection in O-RAN

arXiv:2611.09992v1 Announce Type: new Abstract: Open Radio Access Network (O-RAN) improves radio access network flexibility through disaggregation, open interfaces, and programmable RAN Intelligent Controllers (RICs). However, the same openness and distribution increase the attack surface and make centralized intrusion detection difficult to scale across heterogeneous RAN sites. This paper presents a federated lightweight Transformer framework for privacy-preserving network-layer cyberattack detection in O-RAN. Each participating site trains a compact Transformer locally on temporally ordered network-flow records, while only model parameters are shared with a federated coordinator. To model realistic site heterogeneity, the client datasets are partitioned according to a Dirichlet distribut