Catching Cheats with Interactive Proofs: Privacy-preserving Crowd-sourced Data Collection Without Compromising Integrity

Crowd-sourced sensing systems allow people to voluntarily contribute sensor data from mobile devices. They enable numerous applications, including weather and traffic monitoring. However, their proliferation is at risk if the problems of data integrity and privacy persist. People will be reluctant to contribute sensitive information if they cannot trust the system to maintain their privacy, and the system will be reluctant to accept any data transformed to preserve privacy without proof that the transformation was computed accurately. We present an interactive proof protocol that allows an intermediary to convince a data consumer that it is accurately performing a privacy-preserving transformation with inputs from trusted sources, without providing those inputs to the consumer. We provide soundness and correctness proofs for the protocol, discuss its current limitations, and describe its parameters and their effect on data integrity and privacy when tweaked.