BibTeX for papers by David Kotz; for complete/updated list see
https://www.cs.dartmouth.edu/~kotz/research/papers.html

@InProceedings{cornelius:anonysense,
  author =        {Cory Cornelius and Apu Kapadia and David Kotz and Dan Peebles and Minho Shin and Nikos Triandopoulos},
  title =         {{AnonySense: Privacy-Aware People-Centric Sensing}},
  booktitle =     {{Proceedings of the International Conference on Mobile Systems, Applications, and Services (MobiSys)}},
  year =          2008,
  month =         {June},
  pages =         {211--224},
  publisher =     {ACM},
  copyright =     {ACM},
  DOI =           {10.1145/1378600.1378624},
  URL =           {https://www.cs.dartmouth.edu/~kotz/research/cornelius-anonysense/index.html},
  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. \par  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 \emph{tasks} that will be distributed across anonymous participating mobile devices, later receiving verified, yet anonymized, sensor data \emph{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.},
}