An information-aware privacy-preserving accelerometer data sharing

Abstract

In the age of big data, plenty of valuable data have been shared to enhance scientific innovation, which, however, may disclose unexpected privacy leakage. Although numerous privacy preservation techniques have been proposed to conceal sensitive information, it is usually at the cost of the application utility reduction. In this paper, we present a data sharing scheme, which balances the application utility and privacy leakage for specific data sharing. To illustrate our scheme, smartphones’ acceleration data have been adopted as an illustrative example. Experimental study has shown that sampling frequency play dominant roles in reducing privacy leakage with much less reduction on utility.