Application and analysis of multidimensional negative surveys in participatory sensing applications

  • Authors:
  • Michael M. Groat;Benjamin Edwards;James Horey;Wenbo He;Stephanie Forrest

  • Affiliations:
  • University of New Mexico, Albuquerque, NM 87131, United States;University of New Mexico, Albuquerque, NM 87131, United States;Oak Ridge National Laboratory, Oak Ridge, TN 37831, United States;McGill University, Montreal, Quebec H3A 2T5, Canada;University of New Mexico, Albuquerque, NM 87131, United States and Santa Fe Institute, Santa Fe, NM 87501, United States

  • Venue:
  • Pervasive and Mobile Computing
  • Year:
  • 2013

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Abstract

Participatory sensing applications rely on individuals to share personal data to produce aggregated models and knowledge. In this setting, privacy concerns can discourage widespread adoption of new applications. We present a privacy-preserving participatory sensing scheme based on negative surveys for both continuous and multivariate categorical data. Without relying on encryption, our algorithms enhance the privacy of sensed data in an energy and computation efficient manner. Simulations and implementation on Android smart phones illustrate how multidimensional data can be aggregated in a useful and privacy-enhancing manner.