Anonysense

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Anonysense: privacy-aware people-centric sensing

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International Conference On Mobile Systems, Applications And Services archive
Proceeding of the 6th international conference on Mobile systems, applications, and services table of contents

Breckenridge, CO, USA

SESSION: Privacy and security table of contents

Pages 211-224

Year of Publication: 2008

ISBN:978-1-60558-139-2

Authors

Cory Cornelius	Dartmouth College, Hanover, NH, USA
Apu Kapadia	Dartmouth College, Hanover, NH, USA
David Kotz	Dartmouth College, Hanover, NH, USA
Dan Peebles	Dartmouth College, Hanover, NH, USA
Minho Shin	Dartmouth College, Hanover, NH, USA
Nikos Triandopoulos	University of Aarhus, Århus, Denmark

Sponsors

ACM: Association for Computing Machinery
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

Publisher

ACM New York, NY, USA

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ABSTRACT

Personal mobile devices are increasingly equipped with the capability to sense the physical world (through cameras, microphones, and accelerometers, for example) and the, network world (with Wi-Fi and Bluetooth interfaces). Such devices offer many new opportunities for cooperative sensing applications. For example, users' mobile phones may contribute data to community-oriented information services, from city-wide pollution monitoring to enterprise-wide detection of unauthorized Wi-Fi access points. This people-centric mobile-sensing model introduces a new security challenge in the design of mobile systems: protecting the privacy of participants while allowing their devices to reliably contribute high-quality data to these large-scale applications.

We describe AnonySense, a privacy-aware architecture for realizing pervasive applications based on collaborative, opportunistic sensing by personal mobile devices. AnonySense allows applications to submit sensing tasks that will be distributed across anonymous participating mobile devices, later receiving verified, yet anonymized, sensor data reports back from the field, thus providing the first secure implementation of this participatory sensing model. We describe our trust model, and the security properties that drove the design of the AnonySense system. We evaluate our prototype implementation through experiments that indicate the feasibility of this approach, and through two applications: a Wi-Fi rogue access point detector and a lost-object finder.

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