Application and analysis of multidimensional negative surveys in participatory sensing applications

Michael M. Groat, Benjamin Edwards, James Horey, Wenbo He, Stephanie Forrest

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)372-391
Number of pages20
JournalPervasive and Mobile Computing
Issue number3
StatePublished - Jun 2013
Externally publishedYes


  • Multidimensional data
  • Negative surveys
  • Participatory sensing applications
  • Privacy

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications


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