PEMM: A privacy-aware data aggregation solution for mobile sensing networks

Abstract

By more and more, privacy preservation problem is widely discussed among users and researchers. For mobile sensing network, an imperfect privacy preservation scheme will directly put participants into a dangerous situation. The better privacy protection applied, the better sensing data quality will be achieved. In this paper, we present a privacy-aware data aggregation scheme for mobile sensing networks. We considered both the smart nodes like smart-phone and dumb nodes like wearable device or GPS device. We take the location information and the sensing content into consideration separately. And this thought will make sure the sensing content will be k-anonymous and the accurate location will be protected well either. We use erasure coding technology to slice the sensing data record according to the k-anonymity rules. For the sake of efficiency and stability, we compare two coding technology in two sensing data types and give the experiment results and explanations in detail. After that, we give a social model to describe the social relation and a security data sharing protocol among the participants. The introduction of the participants’ social relation may give a new way to the reputation and data trustworthy evaluation mechanism.