Privacy-Protecting Reputation Management Scheme in IoV-based Mobile Crowdsensing

Abstract

Mobile crowdsensing (MCS) has appeared as a viable solution for data gathering in Internet of Vehicle (IoV). As it utilizes plenty of mobile users to perform sensing tasks, the cost on sensor deployment can be reduced and the data quality can be improved. However, there exist two main challenges for the IoV-based MCS, which are the privacy issues and the existence of malicious vehicles. In order to solve these two challenges simultaneously, we propose a privacy-protecting reputation management scheme in IoV-based MCS. In particular, our privacy-protecting scheme can execute quickly since its complexity is extremely low. The reputation management scheme considers vehicle’s past behaviors and quality of information. In addition, we introduced time fading into the scheme, so that our scheme can detect the malicious vehicles accurately and quickly. Moreover, latency in the IoV must be exceedingly low. With the help of the mobile edge computing (MEC) which is deployed on the base station side and has powerful computing capability, the latency can be greatly reduced to meet the requirements of the IoV. Simulation results demonstrate effectiveness of our reputation management scheme in resisting malicious vehicles, which can assess the reputation value accurately and detect the malicious vehicles quickly while protecting the privacy.