Research Article
Privacy-Preserving Collaborative Blind Macro-Calibration of Environmental Sensors in Participatory Sensing
@ARTICLE{10.4108/eai.15-1-2018.153564, author={Jan-Frederic Markert and Matthias Budde and Gregor Schindler and Markus Klug and Michael Beigl}, title={Privacy-Preserving Collaborative Blind Macro-Calibration of Environmental Sensors in Participatory Sensing}, journal={EAI Endorsed Transactions on Internet of Things}, volume={3}, number={10}, publisher={EAI}, journal_a={IOT}, year={2017}, month={4}, keywords={Participatory Sensing, Location Privacy, Sensor Calibration, Mobile Sensing, Environmental Monitoring, Calibration Rendezvous, Citizen Science, Air Pollution}, doi={10.4108/eai.15-1-2018.153564} }- Jan-Frederic Markert
Matthias Budde
Gregor Schindler
Markus Klug
Michael Beigl
Year: 2017
Privacy-Preserving Collaborative Blind Macro-Calibration of Environmental Sensors in Participatory Sensing
IOT
EAI
DOI: 10.4108/eai.15-1-2018.153564
Abstract
The ubiquity of ever-connected smartphones has lead to new sensing paradigms that promise environmental monitoring in unprecedented temporal and spatial resolution. Everyday people may use low-cost sensors to collect environmental data. However, measurement errors increase over time, especially with low-cost air quality sensors. Therefore, regular calibration is important. On a larger scale and in participatory sensing, this needs be done in-situ. Since for this step, personal sensor data, time and location need to be exchanged, privacy implications arise. This paper presents a novel privacy-preserving multi-hop sensor calibration scheme, that combines Private Proximity Testing and an anonymizing MIX network with cross-sensor calibration based on rendezvous. Our evaluation with simulated ozone measurements and real-world taxicab mobility traces shows that our scheme provides privacy protection while maintaining competitive overall data quality in dense participatory sensing networks.
Copyright © 2017 J.-F. Markert, M. Budde et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
