PriSense: Privacy-Preserving Data Aggregation in People-Centric Urban Sensing Systems

People-centric urban sensing is a new paradigm gaining popularity. A main obstacle to its widespread deployment and adoption are the privacy concerns of participating individuals. To tackle this open challenge, this paper presents the design and evaluation of PriSense, a novel solution to privacypreserving data aggregation in people-centric urban sensing systems. PriSense is based on the concept of data slicing and mixing and can support a wide range of statistical additive and non-additive aggregation functions such as Sum, Average, Variance, Count, Max/Min, Median, Histogram, and Percentile with accurate aggregation results. PriSense can support strong user privacy against a tunable threshold number of colluding users and aggregation servers. The efficacy and efficiency of PriSense are confirmed by thorough analytical and simulation results.

• Type: Journal
• Year: 2010
• Where: INFOCOM
• Authors: Jing Shi, Rui Zhang, Yunzhong Liu, Yanchao Zhang
• Keywords: Communications, INFOCOM 2010, Non-additive Aggregation Functions, People-centric Urban Sensing, Tunable Threshold Number