Paper 2017/1035

Privacy-respecting Reward Generation and Accumulation for Participatory Sensing Applications

Tassos Dimitriou

Abstract

Participatory or crowd-sensing applications process sensory data contributed by users and transform them to simple visualizations (such as for example noise or pollution levels) that help create an accurate representation of the surrounding environment. Although contributed data is of great interest to individuals, the involvement of citizens and community groups, however, is still limited. Hence, incentivizing users to increase participation seems crucial for the success of participatory sensing. In this paper, we develop a privacy-preserving rewarding scheme which allows campaign administrators to reward users for the data they contribute. Our system of anonymous tokens allow users to enjoy the benefits of participation while at the same time ensuring their anonymity. Moreover, rewards can be accumulated together thus further increasing the level of privacy offered by the system. Our proposal is coupled with a security analysis showing the privacy-preserving character of the system along with an efficiency analysis demonstrating the feasibility of our approach in realistic deployment settings.