A Privacy-Preserving Navigation Scheme with Malicious Data Detection in VANETs

Real-time intelligent navigation services can be found everywhere in our daily lives. However, there are many factors that need to be considered when implementing intelligent navigation, such as the security and stability of intelligent navigation services. Most existing state-of-the-art approaches use pseudonymous, public-key fully homomorphic encryption (FHE) to protect location privacy. However, the collected real-time data is not processed in the existing schemes, and malicious data can affect the real-time navigation results. In this paper, we have proposed a privacy-preserving navigation scheme in VANETs that can detect malicious data by using Boolean secret sharing at low cost to filter malicious data and prevent resource abuse. It is also combined with the DTPKC cryptosystem to protect the user’s private information to provide reliable security for the system and ensure that the private information remains hidden from untrustworthy third parties. Meanwhile, the Chinese remainder theorem (CRT) is used in the key generation phase to negotiate the key value between the two parties, and the symmetric key is derived from the key value for sending the navigation results to improve the acquisition efficiency and increase the user experience. We demonstrate the security and practicality of our scheme through SUMO simulation experiments.