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Authentication in a vehicular ad-hoc network (VANET) requires not only secure and efficient authentication with privacy preservation but applicable flexibility to handle complicated transportation circumstances as well. In this paper, we proposed a Two-Factor LIghtweight Privacy-preserving authentication scheme (2FLIP) to enhance the security of VANET communication. 2FLIP employs the decentralized certificate authority (CA) and the biological-password-based two-factor authentication (2FA) to achieve the goals. Based on the decentralized CA, 2FLIP only requires several extremely lightweight hashing processes and a fast message-authentication-code operation for message signing and verification between vehicles. Compared with previous schemes, 2FLIP significantly reduces computation cost by 100–1000 times and decreases communication overhead by 55.24%–77.52%. Furthermore, any certificate revocation list (CRL)-related overhead on vehicles is avoided. 2FLIP makes the scheme resilient to denial-of-service attack in both computation and memory, which is caused by either deliberate invading behaviors or jammed traffic scenes. The proposed scheme provides strong privacy preservation that the adversaries can never succeed in tracing any vehicles, even with all RSUs compromised. Moreover, it achieves strong nonrepudiation that any biological anonym driver could be conditionally traced, even if he is not the only driver of the vehicle. Extensive simulations reveal that 2FLIP is feasible and has an outstanding performance of nearly 0-ms network delay and 0% packet-loss ratio, which are particularly appropriate for real-time emergency reporting applications. [ABSTRACT FROM PUBLISHER]

Roadside infrastructure can greatly help disseminate data to drivers. In this paper, we study a fundamental problem, i.e., roadside infrastructure planning. We propose a class of algorithms named Tailor to select a minimum number of intersections to install the infrastructure. In the case when the traffic information is not available, we formulate the intersection selection problem, which formally proves its np-completeness, and provide novel heuristics, i.e., the adapted-bipartite-based heuristics (ABS), to solve it, whose worst-case approximation ratio is 4/3. ABS bridges the planar graph and the bipartite graph through topology transformation. With ABS, the approximate solution to all the problems that are NP-hard in a general planar graph but polynomially solvable in a bipartite graph can be efficiently obtained in the planar graph. We also prove that, even with traffic information, the intersection selection problem remains NP-hard. Greedy heuristics is employed to balance the tradeoff between the number of selected intersections and the percentage of reached vehicles. [ABSTRACT FROM PUBLISHER]