Anonymous Sensory Data Collection Approach for Mobile Participatory Sensing

In participatory sensing, users with mobile devices participate in the collection of environmental information around them and submit the collected data to a central server for processing and analysis. Identity privacy of mobile users in this model is a major concern that hinders the adoption of this data collection model. In addition, bandwidth and computing capability are limited for mobile devices. Unfortunately, most previously proposed methods for user anonymity are not designed specifically for mobile environments and thus resource constraint is not the main focus of their solutions. In this paper, we propose One-way, an anonymous sensory data collection approach designed particularly for mobile participatory sensing environments. Our method utilizes peer-to-peer networks to facilitate anonymous data transmission to protect sender identity, but the actual data payload is not sent through peers. For data packets, we remove sender information and transmit through a direct path to the server. Since data are not replicated to multiple peers as in some previous solutions, our design consumes less resources. The experiments show that our approach utilizes less bandwidth and achieves higher scalability than existing techniques.