Privacy-Preserving Mechanisms for Crowdsensing: Survey and Research Challenges

Abstract

Crowdsensing (CS) is a new data collection paradigm based on the willingness of people to utilize their mobile devices to sense and transmit data of interest. Given the large amount of cellular users, mobile sensor networks will be able to collect enough data to address large-scale societal problems in a fast, easy, and cost-effective manner. One important issue in CS is that of privacy; without appropriate privacy-preserving mechanisms, many users will not be willing to participate in the data collection process. This paper presents the state-of-the-art in privacy-preserving mechanisms for CS systems. After a general description of CS systems and their main components, this paper addresses the most important issues to consider in the design, implementation, and evaluation of privacy-preserving mechanisms. Then, following a new taxonomy, the most important mechanisms available in the literature are described and qualitatively evaluated. Finally, this paper presents research challenges that should be addressed in order to improve the performance of future privacy-preserving mechanisms for CS systems.