TRAMS: A Secure Vehicular Crowdsensing Scheme Based on Multi-Authority Attribute-Based Signature

Abstract

Recently, vehicular crowdsensing networks have attracted much attention because of their ability to provide efficient and convenient information services for the Internet of Vehicles. How to achieve on-demand message authentication and provide privacy protection of sensing vehicles are challenging in accurate sensing tasks. We propose a secure vehicular crowdsensing scheme based on multi-authority attribute-based signature (TRAMS), which allows the publisher to flexibly customize a fine-grained policy that the potential participants must satisfy and uses attribute-based signature to authenticate sensed messages while protecting the privacy of the sensing vehicle. Also, we propose a multi-authority key management scheme, which can improve vehicle-based sensing efficiency in the Internet of Vehicles. Performance analysis shows that our scheme can not only achieve massage authentication while protecting the privacy of the sensing vehicle, but also ensure fine-grained message authentication to meet the expectation of the publisher on demand. And compared with the single-authority schemes in vehicular communication, our multi-authority TRAMS can achieve efficient message authentication for vehicular crowdsensing applications which require timely task feedback.