Title :
PriSense: Privacy-Preserving Data Aggregation in People-Centric Urban Sensing Systems
Author :
Shi, Jing ; Zhang, Rui ; Liu, Yunzhong ; Zhang, Yanchao
Author_Institution :
Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA
Abstract :
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.
Keywords :
data handling; data privacy; mobile computing; statistics; PriSense; data aggregation; data mixing; data slicing; non-additive aggregation function; people-centric urban sensing; privacy preservation; statistical additive function; Aggregates; Communications Society; Computer architecture; Data privacy; Distributed computing; Histograms; Personal digital assistants; Sensor systems; Space technology; Statistical distributions;
Conference_Titel :
INFOCOM, 2010 Proceedings IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-5836-3
DOI :
10.1109/INFCOM.2010.5462147
