Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2025 (iCAST-ES 2025)

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Federated Learning-empowered Decentralized Cyber Attack Detection for Connected Vehicles Networks

Authors
Ahmad Zainudin1, *, Haryadi Amran Darwito1, Nailul Muna1, Norma Ningsih1
1Department of Electrical Engineering, Politeknik Elektronika Negeri Surabaya, Surabaya, Indonesia
*Corresponding author. Email: zai@pens.ac.id
Corresponding Author
Ahmad Zainudin
Available Online 31 December 2025.
DOI
10.2991/978-94-6463-926-1_64How to use a DOI?
Keywords
Federated learning; decentralized cyber attack detection (DCAT); Internet of Vehicle (IoV); Controller Area Network (CAN) bus protocol; and intra-vehicle vulnerability
Abstract

The integration of the Internet of Things (IoT) into vehicular networks has given rise to a promising new concept known as the Internet of Vehicles (IoV), which is reshaping transportation by enhancing safety and improving mobility efficiency. The Electronic Control Unit (ECU) in IoV most commonly utilizes the Controller Area Network (CAN) bus protocol to exchange data within vehicles. However, without proper authentication and encryption mechanisms, existing CAN bus communications are susceptible to cyber threats, including intra-vehicle vulnerabilities. This paper proposes a decentralized cyber attack detection (DCAT) framework by leveraging the Federated Learning (FL) technique to ensure privacy-preserving connected vehicle data during the distributed learning process. The measurement results present the proposed DCAT framework outperforms the established techniques by providing an accuracy of 98.09%, precision of 87.01%, recall of 85.41%, and f1-score of 85.91%.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2025 (iCAST-ES 2025)
Series
Advances in Engineering Research
Publication Date
31 December 2025
ISBN
978-94-6463-926-1
ISSN
2352-5401
DOI
10.2991/978-94-6463-926-1_64How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Ahmad Zainudin
AU  - Haryadi Amran Darwito
AU  - Nailul Muna
AU  - Norma Ningsih
PY  - 2025
DA  - 2025/12/31
TI  - Federated Learning-empowered Decentralized Cyber Attack Detection for Connected Vehicles Networks
BT  - Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2025 (iCAST-ES 2025)
PB  - Atlantis Press
SP  - 574
EP  - 580
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-926-1_64
DO  - 10.2991/978-94-6463-926-1_64
ID  - Zainudin2025
ER  -