A novel conditional anonymity scheme for vehicular communication networks

Abstract

Vehicular communication networks are traffic applications of the Internet of Things consisting of vehicle nodes, roadside units, service providers, and other components. To protect the vehicle privacy, some vehicular communication networks adopt anonymous schemes. However, in these anonymous schemes, anonymity abuse is inevitable. In order to protect vehicular privacy and prevent anonymity abuse, some conditional anonymous authentication schemes based on cryptography have been proposed. However, most of these methods have complex computation and large communication overhead, which makes them difficult to meet the actual requirement of high-speed traffic in vehicular communication networks. In this paper, a novel conditional anonymity scheme called VKPCA (vehicular communication network based on kernel principal component analysis [KPCA]) is proposed, which can protect vehicle privacy while avoid anonymity abuse. The simulation results show that this scheme has lower computational complexity and communication overhead than the conventional anonymous authentication scheme.

A Survey of Location Privacy Preservation in Social Internet of Vehicles

“…This approach utilizes a pseudonym management scheme based on fog computing, which has abundant network edge resources; accordingly, the method can transfer the pseudonym management system to the fog, which is composed of roadside units (RSUs), and proposes the concept of pseudonyms change choice pseudonyms problem, which can effectively reduce costs and ensure that the user attribute information is safe without creating delays in data transmission. Moreover, in order to solve the problem of computing complexity, Wang et al used the dimension reduction method to manage the pseudonyms [45]; this reduces both the time cost and space complexity of vehicle certifications, while the new condition of anonymous VKPCA (vehicular communication network based on kernel principal component analysis) is also implemented to avoid abuse of the anonymities at the same time. This approach has lower computational complexity, while also being able to protect the user attribute information.…”

“…This section identifies three future research directions in the field of location privacy protection. [28]- [45] Low overhead and simple implementation Low user service availability K-anonymous [28] Pseudonym [38] Location privacy protection policy based on user behavior information [46]- [75] High degree of privacy protection…”