@inproceedings{2da317256775407b833dc670abb348fd,
title = "V2V Communications Using Blockchain-Enabled 6G Technology and Federated Learning",
abstract = "This study proposes an interesting approach for vehicle-to-vehicle (V2V) communication, which integrates blockchain technology, federated learning (FL), and allocation optimization of latency and resources. The research evaluates the proposed system using various performance metrics such as packet delivery ratio (PDR), model accuracy, and latency and demonstrates its superiority over existing techniques. Further-more, the system provides enhanced security through consensus optimization and k-anonymity for data privacy. Overall, the proposed system is a promising solution for efficient and secure V2V communication in the era of connected and autonomous vehicles. Moreover, the proposed approach achieves higher reli-ability, lower latency, and better resource utilization compared to traditional 5G.",
keywords = "Beyond 5G, Blockchain, Federated Learning, SG/6G, V2V",
author = "Ahmed, \{Tahir H.\} and Tiang, \{Jun Jiat\} and Azwan Mahmud and Do, \{Dinh Thuan\} and Truong Tran and Shahid Mumtaz",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Global Communications Conference, GLOBECOM 2023 ; Conference date: 04-12-2023 Through 08-12-2023",
year = "2023",
doi = "10.1109/GLOBECOM54140.2023.10437406",
language = "English",
series = "Proceedings - IEEE Global Communications Conference, GLOBECOM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1302--1307",
booktitle = "GLOBECOM 2023 - 2023 IEEE Global Communications Conference",
address = "United States",
}