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A Hybrid Approach for Efficient Privacy-Preserving Authentication in VANET - 2017

Research Area:  Vehicular Ad Hoc Networks


A vehicular ad hoc network (VANET) serves as an application of the intelligent transportation system that improves traffic safety as well as efficiency. Vehicles in a VANET broadcast traffic and safety-related information used by road safety applications, such as an emergency electronic brake light. The broadcast of these messages in an open-access environment makes security and privacy critical and challenging issues in the VANET. A misuse of this information may lead to a traffic accident and loss of human lives at worse and, therefore, vehicle authentication is a necessary requirement. During authentication, a vehicles privacy-related data, such as identity and location information, must be kept private. This paper presents an approach for privacy-preserving authentication in a VANET. Our hybrid approach combines the useful features of both the pseudonym-based approaches and the group signature-based approaches to preclude their respective drawbacks. The proposed approach neither requires a vehicle to manage a certificate revocation list, nor indulges vehicles in any group management. The proposed approach utilizes efficient and lightweight pseudonyms that are not only used for message authentication, but also serve as a trapdoor in order to provide conditional anonymity. We present various attack scenarios that show the resilience of the proposed approach against various security and privacy threats. We also provide analysis of computational and communication overhead to show the efficiency of the proposed technique. In addition, we carry out extensive simulations in order to present a detailed network performance analysis. The results show the feasibility of our proposed approach in terms of end-to-end delay and packet delivery ratio.

Author(s) Name:  Ubaidullah Rajput; Fizza Abbas; Hasoo Eun and Heekuck Oh

Journal name:  IEEE Access

Conferrence name:  

Publisher name:  IEEE

DOI:  10.1109/ACCESS.2017.2717999

Volume Information:  ( Volume: 5) Page(s): 12014 - 12030