A Competitiveness-driven and Secure Incentive Mechanism for Competitive Organizations Data Sharing: A Contract Theoretic Approach

In the era of big data and artificial intelligence, data sharing is desirable for vigorous development of data-driven intelligent services. Although data sharing is supported to a certain extent by current mechanisms and technologies, organizations especially with potential competitive relationships might refuse to share their data. One reason is that data holders worry that data sharing improves competitors' competitiveness. The other reason is that data sharing suffers huge privacy security risk. To address these problems, in this paper, the concept of competitiveness is introduced as a data sharing transaction driving force to eliminate the competitiveness worry of data holders while differential privacy is adopt to protect their privacy. As there is an information asymmetry between data sharers and data demanders, a contract theoretic approach is proposed to motivate data holders to share data with privacy protection, which is expected to achieve a target of win-win and data sharing security. By designing optimal contracts, the data demander can decide rationally how to pay the data holders given the privacy parameter. Moreover, data holders can choose the contract that maximize their utilities. Numerical results substantiate the effectiveness of the the proposed scheme.