Raw Data Truthfulness and Privacy Preservation in a Practical Data Market

Abstract

In the era of block chain, ensuring data truthfulness and protecting the privacies of data contributors are both important to the long term healthy development of data markets. On one hand, the ultimate goal of the service provider in a data market is to maximize their profit. Yet, to reduce operation cost, a strategic service provider may provide data services based on the whole raw data set, or even return a fake result without processing the data from designated data sources. The content of raw data should not be disclosed to data consumers to guarantee data confidentiality, even if the real identities of the data contributors are hidden. TPDM is structured internally in associate degree Encrypt-then-Sign fashion, using partially homomorphic encryption and identity-based signature. It at the same time facilitates batch verification, data processing, and outcome verification, while maintaining identity preservation and data confidentiality. We additionally instantiate TPDM with a profile matching service and an information distribution service, and extensively evaluate their performances