NDLI: On the efficiency of privacy-preserving path hiding for mobile sensing applications

Content Provider	IEEE Xplore Digital Library
Author	Christin, D. Reinhardt, A. Hollick, M.
Copyright Year	2013
Description	Author affiliation: Secure Mobile Networking Lab., Tech. Univ. Darmstadt, Darmstadt, Germany (Christin, D.; Hollick, M.) \|\| Sch. of Comput. Sci. & Eng., Univ. of New South Wales, Sydney, NSW, Australia (Reinhardt, A.)
Abstract	Current mobile sensing applications typically annotate the collected sensor readings with spatiotemporal information before reporting them to a central server. Such information can however endanger the users' privacy, as it reveals insights about their daily routines. Users must therefore trust the application administrators not to misuse the reported information. To diminish user dependence on administrators trustworthiness, we propose a privacy-preserving collaborative scheme, in which users exchange the collected sensor readings at opportunistic encounters. We model malicious administrators attempting to identify exchanged sensor readings based on spatial disparity by applying four state-of-the-art outlier detection algorithms. We thoroughly investigate the influence of different exchange patterns and the parameters of the algorithms on their performance based on a real-world dataset. The results for location traces of 20 users gathered during 14 days show that our algorithm achieves a high level of privacy protection.
Starting Page	818
Ending Page	826
File Size	1755105
Page Count	9
File Format	PDF
ISSN	07421303
e-ISBN	9781479905379
DOI	10.1109/LCN.2013.6761337
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-21
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Privacy Servers Detection algorithms Sensors Spatiotemporal phenomena Computational modeling Conferences security and privacy protection Mobile applications
Content Type	Text
Resource Type	Article

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