Sezaki & Nishiyama Laboratory
Institute of Industrial Science / Center for Spatial Information Science in The University of Tokyo
Institute of Industrial Science / Center for Spatial Information Science in The University of Tokyo
Shunsuke Aoki, Masayuki Iwai, Kaoru Sezaki
Limited Negative Surveys: Privacy-preserving participatory sensing Inproceedings
In: 2012 IEEE 1st International Conference on Cloud Networking (CLOUDNET), 28-30 Nov. 2012, Paris, France, pp. 158-160, 2012, ISBN: 978-1-4673-2797-8.
Abstract | BibTeX | Tags: Base stations, Data privacy, Educational institutions, Mobile handsets, Privacy, Protocols, sensors | Links:
@inproceedings{6483674,
title = {Limited Negative Surveys: Privacy-preserving participatory sensing},
author = {Shunsuke Aoki and Masayuki Iwai and Kaoru Sezaki},
doi = {10.1109/CloudNet.2012.6483674},
isbn = {978-1-4673-2797-8},
year = {2012},
date = {2012-01-01},
booktitle = {2012 IEEE 1st International Conference on Cloud Networking (CLOUDNET), 28-30 Nov. 2012, Paris, France},
journal = {2012 1st IEEE International Conference on Cloud Networking, CLOUDNET 2012 - Proceedings},
pages = {158-160},
abstract = {Participatory sensing is a crowd-sourcing technique that relies on participants' active contribution. By aggregating data sets from each participant, we can collect statistical information of the environment or phenomenona in the cloud. To promote use of participatory sensing in healthcare, research, and other useful applications, the protection of privacy is important to consider. The invasion of privacy in participatory sensing would have dire consequences because mobile phone used by these applications have sensitive data about users daily life. In this paper, we suggest a privacy-preserving participatory sensing scheme for real-world data sets with large numbers of categories by using Limited Negative Surveys. By using our method described in this paper, the server can reconstruct the probability distributions of the original distributions of sensed values without knowing the personal information of citizens. Furthermore, our research has the capablity to change, according to the features of data, especially the number of categories. We evaluate how this scheme of aggregate information can be still useful while protecting the privacy of users' original data.},
keywords = {Base stations, Data privacy, Educational institutions, Mobile handsets, Privacy, Protocols, sensors},
pubstate = {published},
tppubtype = {inproceedings}
}