Accomplishing Data Truthfulness and Confidentiality in Large Scale Data Markets

Abstract

Due to the advent of new technologies, devices, and communication, the data generated by the human is growing rigorously, along with the data, the use of person-specific data is increasing. The service provider extracts basic data from the contributors and trades it for the data consumers. But the major problem is the data truthfulness. To overcome this problem, this paper introduces a framework called Truthfulness and confidentiality in Data Markets (TCDM), which verifies the truthfulness in data collection as well as in data processing and provides quality-added data to the consumers. Most of the contributors do not want to reveal their private information to the data consumers. TCDM provides security to the contributors by using a meddle proof-device. TCDM provides truthfulness and confidentiality using homomorphic encryption and identity-based encryption. TCDM follows Encrypt-then-Sign fashion to attain truthfulness. It simultaneously, provides batch verification, outcome verification, data processing, etc. Finally, TCDM can achieve all the tasks with low computational and communicational overheads.

Keywords: Data truthfulness, meddle-proof device, confidentiality, Privacy, encryption.