{"ID":2824075,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.24345","arxiv_id":"2512.24345","title":"FedSecureFormer: A Fast, Federated and Secure Transformer Framework for Lightweight Intrusion Detection in Connected and Autonomous Vehicles","abstract":"This works presents an encoder-only transformer built with minimum layers for intrusion detection in the domain of Connected and Autonomous Vehicles using Federated Learning.","short_abstract":"This works presents an encoder-only transformer built with minimum layers for intrusion detection in the domain of Connected and Autonomous Vehicles using Federated Learning.","url_abs":"https://arxiv.org/abs/2512.24345","url_pdf":"https://arxiv.org/pdf/2512.24345v1","authors":"[\"Devika S\",\"Vishnu Hari\",\"Pratik Narang\",\"Tejasvi Alladi\",\"F. Richard Yu\"]","published":"2025-12-30T16:55:19Z","proceeding":"cs.CR","tasks":"[\"cs.CR\",\"cs.AI\"]","methods":"[\"Transformer\"]","has_code":false}