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2022-11-22
Farran, Hassan, Khoury, David, Kfoury, Elie, Bokor, László.  2021.  A blockchain-based V2X communication system. 2021 44th International Conference on Telecommunications and Signal Processing (TSP). :208—213.
The security proposed for Vehicle-to-Everything (V2X) systems in the European Union is specified in the ETSI Cooperative Intelligent Transport System (C-ITS) standards, and related documents are based on the trusted PKI/CAs. The C-ITS trust model platform comprises an EU Root CA and additional Root CAs run in Europe by member state authorities or private organizations offering certificates to individual users. A new method is described in this paper where the security in V2X is based on the Distributed Public Keystore (DPK) platform developed for Ethereum blockchain. The V2X security is considered as one application of the DPK platform. The DPK stores and distributes the vehicles, RSUs, or other C-ITS role-players’ public keys. It establishes a generic key exchange/ agreement scheme that provides mutual key, entity authentication, and distributing a session key between two peers. V2X communication based on this scheme can establish an end-to-end (e2e) secure session and enables vehicle authentication without the need for a vehicle certificate signed by a trusted Certificate Authority.
2018-05-02
Gu, P., Khatoun, R., Begriche, Y., Serhrouchni, A..  2017.  k-Nearest Neighbours classification based Sybil attack detection in Vehicular networks. 2017 Third International Conference on Mobile and Secure Services (MobiSecServ). :1–6.

In Vehicular networks, privacy, especially the vehicles' location privacy is highly concerned. Several pseudonymous based privacy protection mechanisms have been established and standardized in the past few years by IEEE and ETSI. However, vehicular networks are still vulnerable to Sybil attack. In this paper, a Sybil attack detection method based on k-Nearest Neighbours (kNN) classification algorithm is proposed. In this method, vehicles are classified based on the similarity in their driving patterns. Furthermore, the kNN methods' high runtime complexity issue is also optimized. The simulation results show that our detection method can reach a high detection rate while keeping error rate low.

2015-05-05
Eckhoff, D., Sommer, C..  2014.  Driving for Big Data? Privacy Concerns in Vehicular Networking Security Privacy, IEEE. 12:77-79.

Communicating vehicles will change road traffic as we know it. With current versions of European and US standards in mind, the authors discuss privacy and traffic surveillance issues in vehicular network technology and outline research directions that could address these issues.