Achieving Data Truthfulness and Privacy Preservation in Data Markets

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Aim:

The main aim of this project to provide effective survey that guarantees data truthfulness and privacy preservation.

Proposed system:

In the era of big data, society has developed an insatiable appetite for sharing personal data. Realizing the potential of personal data’s economic value in decision making and user experience enhancement, several open information platforms have emerged to enable person-specific data to be exchanged on the Internet. For example social enterprise API platform, collects social media data from users, mines deep insights into customized audiences, and provides data analysis solutions to more than 95% of the Fortune. In this project, we have proposed the first efficient secure scheme TPDM for data markets, which simultaneously guarantees data truthfulness and privacy preservation. In TPDM, the data contributors have to truthfully submit their own data, but cannot impersonate others. Besides, the service provider is enforced to truthfully collect and process data. Furthermore, both the personally identifiable Information and the sensitive raw data of data contributors are well protected. In addition, we have instantiated TPDM with two different data services, and extensively evaluated their performances on two real-world datasets.