Vehicular ad hoc networks (VANET) authorize the vehicles to communicate and exchange data among themselves and with the Road-Side Unit (RSU). However, with the increase of the vehicles number, the VANET become vulnerable to many attacks. One serious attack is the Sybil attack which threats the functionalities of VANET by generating a high number of fake identities. In this paper, we present a Multi-Levels Trust Mechanism solution (BMLT-SA) based on the blockchain to detect the Sybil attack. Our approach is divided into three main parts : (1) A Horizontal Trust Management mechanism (HTM) is introduced as vehicle to vehicle (V2V) scheme to detect a malicious vehicle. In this level, each vehicle runs a Local Machine Learning (LML) algorithm to classify their neighbors as normal and malicious ones. All the decisions made by the vehicles are broadcasted to the RSUs; (2) A Vertical Trust Management mechanism (VTM) is used to launch a verification algorithm by the RSU. This algorithm takes as input all the LML results and gives a Vehicular Trust list as output; (3) All the RSUs belonging to the same region are collaborating to form a Distributed Trust Management mechanism (DTM) based on the use of the blockchain to share the Vehicular Trust List and to identify the class of each vehicle crossing the network. Simulations and experiments demonstrate that the proposed model based on the collaboration of different VANET components is an effective method for Sybil attack detection.
Blockchain-based Multi-Levels Trust Mechanism Against Sybil Attacks for Vehicular Networks
01.12.2020
1339581 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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