@inproceedings{09455ea30922497d9c6094bf349ccf3b,
title = "A machine learning based approach for the detection of sybil attacks in C-ITS",
abstract = "The intrusion detection systems are vital for the sustainability of Cooperative Intelligent Transportation Systems (C-ITS) and the detection of sybil attacks are particularly challenging. In this work, we propose a novel approach for the detection of sybil attacks in C-ITS environments. We provide an evaluation of our approach using extensive simulations that rely on real traces, showing our detection approach's effectiveness.",
keywords = "C-ITS, Certificate, PKI, Privacy, Pseudonym, Security, Sybil attack, VANET",
author = "Badis Hammi and Idir, \{Mohamed Yacine\} and Rida Khatoun",
note = "Publisher Copyright: {\textcopyright} 2022 IEICE.; 23rd Asia-Pacific Network Operations and Management Symposium, APNOMS 2022 ; Conference date: 28-09-2022 Through 30-09-2022",
year = "2022",
month = jan,
day = "1",
doi = "10.23919/APNOMS56106.2022.9919991",
language = "English",
series = "APNOMS 2022 - 23rd Asia-Pacific Network Operations and Management Symposium: Data-Driven Intelligent Management in the Era of beyond 5G",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "APNOMS 2022 - 23rd Asia-Pacific Network Operations and Management Symposium",
}