A Privacy-preserving Aggregation Scheme Based On Negative Survey For Vehicle Fuel Consumption Data

Abstract The vehicle fuel consumption gauge is a vehicle’s basic device that usually records the instan- taneous as well as average fuel consumption of the vehicle, which brings a lot of convenience during the driving process. The individual real-time fuel consumption data are meaningless, but its continuous real-time fuel consumption data contains some information that may reveal the user’s privacy, which is sensitive information for users. There are hot topics on privacy protection of sensitive user information, however, most of the studies have focused on privacy protection at the time of data release and the need for a trusted third party. In this paper, we propose a negative survey-based approach that can be utilized to protect aggregated vehicle fuel consumption data against time-series-based differential attacks. Its anonymous algorithm on the user side and es- timation algorithm on the server side are able to protect the user’s privacy regardless of changes in the user’s fuel consumption data. The experiment results show that our method can achieve better privacy protection with better application prospects in a simpler and more effective way.