Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
463937 | Pervasive and Mobile Computing | 2013 | 20 Pages |
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.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Michael M. Groat, Benjamin Edwards, James Horey, Wenbo He, Stephanie Forrest,