Research Article
Privacy-Preserving Online Mixing of High Integrity Mobile Multi-user Data
@INPROCEEDINGS{10.1007/978-3-642-31909-9_28, author={Akshay Dua and Nirupama Bulusu and Wu-chang Feng}, title={Privacy-Preserving Online Mixing of High Integrity Mobile Multi-user Data}, proceedings={Security and Privacy in Communication Networks. 7th International ICST Conference, SecureComm 2011, London, UK, September 7-9, 2011, Revised Selected Papers}, proceedings_a={SECURECOMM}, year={2012}, month={10}, keywords={privacy integrity interactive proofs participatory sensing}, doi={10.1007/978-3-642-31909-9_28} }- Akshay Dua
Nirupama Bulusu
Wu-chang Feng
Year: 2012
Privacy-Preserving Online Mixing of High Integrity Mobile Multi-user Data
SECURECOMM
Springer
DOI: 10.1007/978-3-642-31909-9_28
Abstract
Crowd-sourced sensing systems facilitate unprecedented insight into our local environments by leveraging voluntarily contributed data from the impressive array of smartphone sensors (GPS, audio, image, accelerometer, etc.). However, user participation in crowd-sourced sensing will be inhibited if people cannot trust the system to maintain their privacy. On the other hand, data modified for privacy may be of limited use to the system without mechanisms to verify integrity. In this paper, we present an interactive proof protocol that allows an intermediary to convince a data consumer that it is accurately performing a privacy-preserving transformation mixing inputs from multiple expected sources, but without revealing those inputs. Additionally, we discuss privacy transformation functions that are compatible with the protocol, and show that the protocol introduces very little overhead, making it ideal for real-time crowd-sourced data collection.