As an indispensable part of intelligent transportation systems, Internet of Vehicles (IoV) has been widely used in improving the driving experience and road conditions. In the communication of IoV, the security of transmitted messages is critical. Specifically, the messages should be signed and verified before they are accepted by vehicles or road side units. To ensure the privacy of vehicle users, the vehicles’ true identity cannot be leaked. Moreover, considering the high dynamics and open environments of IoV, it is very important to design an efficient anonymous authentication scheme on the basis of security. However, most of the existing schemes struggle with the problems of insufficient security performance and low efficiency. This motivates us to propose a safe and efficient privacy protection scheme for IoV. The proposed scheme is a new batch anonymous authentication scheme designed based on the elliptic curve encryption algorithm, considering both security and efficiency. A distributed signature generation method is also developed in the proposed scheme to relieve the burden of the trusted center. In addition, our scheme can effectively track illegal vehicles and achieve conditional privacy protection. Theoretical analysis and performance evaluation are both carried out to validate our scheme. The results show that our scheme ensures competitive security performance with lower communication and computation overheads compared to representative approaches.

作为智能交通系统必不可少的一部分，车联网（IoV）已被广泛用于改善驾驶体验和路况。在IoV的通信中，传输消息的安全性至关重要。具体来说，在车辆或路边单位接受消息之前，应对消息进行签名和验证。为了确保车辆使用者的隐私，车辆的真实身份不能被泄露。此外，考虑到IoV的高动态性和开放环境，基于安全性设计有效的匿名身份验证方案非常重要。但是，大多数现有方案都存在安全性能不足和效率低下的问题。这促使我们为IoV提出安全有效的隐私保护方案。该方案是一种基于椭圆曲线加密算法并兼顾安全性和效率的新型批量匿名认证方案。在该方案中还开发了一种分布式签名生成方法，以减轻可信中心的负担。此外，我们的计划可以有效地跟踪非法车辆并实现有条件的隐私保护。进行了理论分析和性能评估，以验证我们的方案。结果表明，与具有代表性的方法相比，我们的方案以较低的通信和计算开销确保了具有竞争力的安全性能。在该方案中还开发了一种分布式签名生成方法，以减轻可信中心的负担。此外，我们的计划可以有效地跟踪非法车辆并实现有条件的隐私保护。进行了理论分析和性能评估，以验证我们的方案。结果表明，与具有代表性的方法相比，我们的方案以较低的通信和计算开销确保了具有竞争力的安全性能。在该方案中还开发了一种分布式签名生成方法，以减轻可信中心的负担。此外，我们的计划可以有效地跟踪非法车辆并实现有条件的隐私保护。进行了理论分析和性能评估，以验证我们的方案。结果表明，与具有代表性的方法相比，我们的方案以较低的通信和计算开销确保了具有竞争力的安全性能。