Abstract: Personal mobile devices are increasingly equipped with the capability to sense the physical world (through cameras, microphones, accelerometers, and light sensors, for example) and the network world (with Wi-Fi and Bluetooth interfaces). Mobile phones or other personal devices offer many new opportunities for cooperative sensing applications. In such applications, the sensors 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 sensor-networking model introduces a new security challenge in mobile-systems design: 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 large-scale 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 detector and a lost-object finder.
Keywords: mobile computing, sensor network, pervasive computing, security, privacy, anonymity, urban sensing, ubicomp, dfk
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Copyright © 2008 by the authors.