A machine learning based approach for the detection of sybil attacks in C-ITS
Author
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.

Year of Publication
2022
Conference Name
2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS)
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