Kangsoo Jung  Seog Park

10.5626/JOK.2019.46.4.376

Differential privacy Data Market matching theory negotiation theory

Digital data is currently an indispensable resource for making effective decisions. As the value of digital data is increasing, digital markets, where data providers and consumers can deal with data, are also attracting attention as a mean of obtaining that data. However, obtaining the digital data can lead to privacy breaches, which affects individuals’ willingness to provide data. In this study, a fair negotiation method that can set the appropriate price and noise parameter εconsidering the data provider and the consumer in the differentially private data market environment was proposed. A data market framework with a market manager that links the data provider and the consumer is suggested. In addition, a technique of determining the price and noise parameter ε of the data in two phases using matching theory and Rubinstein bargaining is proposed. It is established that the proposed negotiation technique provides an appropriate level of ε and unit price, which satisfy the data provider and the consumer. The proposed technique prevents unfair transactions and can determine the appropriate level of ε and unit price.