Privacy for real-time location-based services
SIGSPATIAL Special
A survey of computational location privacy
Personal and Ubiquitous Computing
Trust-based data disclosure in sensor networks
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Personal data vaults: a locus of control for personal data streams
Proceedings of the 6th International COnference
Location privacy and resilience in wireless sensor networks querying
Computer Communications
Privacy-aware collection of aggregate spatial data
Data & Knowledge Engineering
Application and analysis of multidimensional negative surveys in participatory sensing applications
Pervasive and Mobile Computing
Secure and energy-efficient data aggregation for wireless sensor networks
International Journal of Mobile Network Design and Innovation
Classifying and clustering in negative databases
Frontiers of Computer Science: Selected Publications from Chinese Universities
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Sensor networks involving human participants will require privacy protection before wide deployment is feasible. This paper proposes and evaluates a set of protocols that enable anonymous data collection in a sensor network. Sensor nodes, instead of transmitting their actual data, transmit a sample of the data complement to a basestation. The basestation then uses the negative samples to reconstruct a histogram of the original sensor readings. These protocols, collectively defined as a negative survey, are computationally simple and do not increase communication overhead. Thus, the negative survey can be implemented efficiently on existing sensor network platforms. We analyze the accuracy of the negative survey under a variety of conditions and define a range of parameter values for which it is practical. We also describe an example traffic monitoring application that uses the negative survey to classify traffic behavior. We demonstrate that for reasonable traffic scenarios, the system accurately classifies traffic behavior without revealing private information.