TY - GEN
T1 - Anonymous data collection in sensor networks
AU - Horey, James
AU - Groat, Michael M.
AU - Forrest, Stephanie
AU - Esponda, Fernando
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=50249126583&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=50249126583&partnerID=8YFLogxK
U2 - 10.1109/MOBIQ.2007.4451016
DO - 10.1109/MOBIQ.2007.4451016
M3 - Conference contribution
AN - SCOPUS:50249126583
SN - 1424410258
SN - 9781424410255
T3 - Proceedings of the 4th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2007
BT - Proceedings of the 4th Annual International Conference on Mobile and Ubiquitous Systems
T2 - 4th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2007
Y2 - 6 August 2007 through 10 August 2007
ER -