Zero-knowledge identity authentication for internet of vehicles: Improvement and application.

The popularity of Internet of Vehicles (IoV) has made people's driving environment more comfortable and convenient. However, with the integration of external networks and the vehicle networks, the vulnerabilities of the Controller Area Network (CAN) are exposed, allowing attackers to remotely invade vehicle networks through external devices. Based on the remote attack model for vulnerabilities of the in-vehicle CAN, we designed an efficient and safe identity authentication scheme based on Feige-Fiat-Shamir (FFS) zero-knowledge identification scheme with extremely high soundness. We used the method of zero-one reversal and two-to-one verification to solve the problem that FFS cannot effectively resist guessing attacks. Then, we carried out a theoretical analysis of the scheme's security and evaluated it on the software and hardware platform. Finally, regarding time overhead, under the same parameters, compared with the existing scheme, the scheme can complete the authentication within 6.1ms without having to go through multiple rounds of interaction, which reduces the additional authentication delay and enables all private keys to participate in one round of authentication, thereby eliminating the possibility that a private key may not be involved in the original protocol. Regarding security and soundness, as long as private keys are not cracked, the scheme can resist guessing attacks, which is more secure than the existing scheme.

Anonymous-authentication scheme based on fog computing for VANET.

Privacy protection in vehicular ad hoc networks (VANETs) has always been a research hotspot, especially the issue of vehicle authentication, which is critical to ensure the safe communication of vehicles. However, using the real identity in the process of authentication can easily result in a leak of the privacy information of the vehicles. Therefore, most existing privacy-protection schemes use anonymous authentication and require one-to-one communication between vehicles and the trusted authority (TA). However, when the number of vehicles is too large, network congestion can take place. In addition, the process of updating the anonymous by the TA or the vehicle itself, can result in both poor real-time performance and leakage of the system master key. To solve these problems, this study proposes a fog-computing-based anonymous-authentication scheme for VANETs; the scheme reduces the communication burden of the TA by enabling self-authentication between vehicles and road-side units (RSUs), thus improving the vehicle-authentication efficiency. For updating the anonymous, we design a fog-computing-based pseudonym-updating and -tracking strategy, which guarantees real-time communication and reduces the instances of re-authentication interactions for legitimate vehicles. The experimental results show that the scheme not only meets the privacy-protection requirements of VANETs but also offers better performance than that of the existing anonymous-authentication schemes.