A Privacy-Preserving Metro Passenger Flow Acquisition and Query System based on Crowd-Sensing

Crowd-sensing applications, such as traffic monitoring and environmental detection, have brought great convenience to people's lives, but they also face with some problems, for example, participant's privacy leakage at sensing phase, querier's privacy leakage at service phase, and so on. However, the existing privacy protection solutions are difficult to solve the above problems simultaneously. In response to this situation, we design a privacy-preserving metro passenger flow acquisition and query system that can settle these issues simultaneously. Our system can not only provide the metro passenger flow query service, which makes it convenient for the people, but also protect the participant's identity and location privacy as well as querier's query privacy. We exploit the Paillier cryptosystem, pseudonym mechanism, and Secure kNN to achieve these properties in our system. Besides, we also realized the participant accountability, which means that a malicious participant can be banned from participating in the system tasks and prosecuted if he/she is detected to "pollutes" the aggregation results. The privacy analysis and experiments demonstrate that our system is practical and meet the privacy preserving and security requirement.