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

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4 Author(s)
Jing Shi ; Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA ; Yanchao Zhang ; Yunzhong Liu ; Yanchao Zhang

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 privacy-preserving 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.

Published in:

INFOCOM, 2010 Proceedings IEEE

Date of Conference:

14-19 March 2010