JAVA PROJECT
Achieving Data
Truthfulness and Privacy Preservation in Data Markets
Abstract:
As a significant business paradigm, many
online information platforms have emerged to satisfy society's needs for
person-specific data, where a service provider collects raw data from data
contributors, and then offers value-added data services to data consumers.
However, in the data trading layer, the data consumers face a pressing problem,
i.e., how to verify whether the service provider has truthfully collected and
processed data? Furthermore, the data contributors are usually unwilling to
reveal their sensitive personal data and real identities to the data consumers.
In this paper, we propose TPDM, which efficiently integrates Truthfulness and
Privacy preservation in Data Markets. TPDM is structured internally in an
Encrypt-then-Sign fashion, using partially homomorphic encryption and
identity-based signature. It simultaneously facilitates batch verification,
data processing, and outcome verification, while maintaining identity
preservation and data confidentiality. We also instantiate TPDM with a profile
matching service and a data distribution service, and extensively evaluate
their performances on Yahoo! Music ratings dataset and 2009 RECS dataset,
respectively. Our analysis and evaluation results reveal that TPDM achieves
several desirable properties, while incurring low computation and communication
overheads when supporting large-scale data markets.
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