CPAHP: Conditional Privacy-Preserving Authentication Scheme With Hierarchical Pseudonym for 5G-Enabled IoV
Jingwei Liu, Chuntian Peng, Rong Sun, Lei Liu, Ning Zhang, Schahram Dustdar, Victor C. M. Leung
Abstract
As a representative application scenario of the Internet of Things (IoT), the Internet of Vehicles (IoV) plays an important function in the area of intelligent transportation. However, data traffic exchanged in IoV is usually correlated with plenty of sensitive information, thus leading to privacy leakage. Nevertheless, if all personal data about vehicles are completely protected, it will be hard to trace the real identities of malicious vehicles, which also raises other security issues in IoV. In addition, existing schemes are not fully suitable for 5G-enabled IoV due to their complex structure and high computation requirements. In order to realize more efficient communication and anonymous authentication of vehicles with superior security, we propose a conditional privacy-preserving authentication scheme with hierarchical pseudonyms (CPAHP) in 5G-enabled IoV, which is based on the elliptic curve Diffie-Hellman (ECDH) problem. Through the hierarchical pseudonym mechanism, CPAHP can protect the real identities and movement tracks of vehicles. Whereas, if vehicles have malicious behaviors, their real identities can be recovered through the corresponding pseudonyms. Furthermore, by taking advantage of a batch verification method, receivers can easily cope with a huge influx of messages in a short space of time. Moreover, by introducing blockchain technology, traffic information can be shared smoothly among all vehicles. Through the security analysis and performance evaluation, it is demonstrated that CPAHP can not only meet the security requirements but also provide higher computational efficiency.