title: PAVS: A New Privacy-Preserving Data Aggregation Scheme for Vehicle Sensing Systems.
abstract: Air pollution has become one of the most pressing environmental issues in recent years. According to a World Health Organization (WHO) report, air pollution has led to the deaths of millions of people worldwide. Accordingly, expensive and complex air-monitoring instruments have been exploited to measure air pollution. Comparatively, a vehicle sensing system (VSS), as it can be effectively used for many purposes and can bring huge financial benefits in reducing high maintenance and repair costs, has received considerable attention. However, the privacy issues of VSS including vehicles' location privacy have not been well addressed. Therefore, in this paper, we propose a new privacy-preserving data aggregation scheme, called PAVS, for VSS. Specifically, PAVS combines privacy-preserving classification and privacy-preserving statistics on both the mean E(·) and variance Var(·), which makes VSS more promising, as, with minimal privacy leakage, more vehicles are willing to participate in sensing. Detailed analysis shows that the proposed PAVS can achieve the properties of privacy preservation, data accuracy and scalability. In addition, the performance evaluations via extensive simulations also demonstrate its efficiency.
authors.affiliation: School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China. xuchang@bit.edu.cn.|School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore. xuchang@bit.edu.cn.
authors.forename: Chang
authors.initials: C
authors.lastname: Xu
authors.affiliation: Faculty of Computer Science, University of New Brunswick, Fredericton, NB E3B 5A3, Canada. rxlu@ieee.org.
authors.forename: Rongxing
authors.initials: R
authors.lastname: Lu
authors.affiliation: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore. hxwang@ntu.edu.sg.
authors.forename: Huaxiong
authors.initials: H
authors.lastname: Wang
authors.affiliation: School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China. liehuangz@bit.edu.cn.
authors.forename: Liehuang
authors.initials: L
authors.lastname: Zhu
authors.affiliation: Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada. c225huan@uwaterloo.ca.
authors.forename: Cheng
authors.initials: C
authors.lastname: Huang
keywords: data aggregation; privacy-preserving aggregation; privacy-preserving data statistics; vehicle sensing