Research and application of innovative models for public data integration based on secure multi-party computation - Jiahe JIN; Chengyao ZHAO; Haoze QIU; Peng LIU (大数据)
Secure multi-party computation is widely used in finance, the Internet, and other fields to solve the problem of ＆quot;data silos＆quot;, but its application in the field of public data is not yet mature.An innovative model for public data integration based on secure multi-party computation was proposed, and a technical architecture for joint computing using public data from different parties while protecting their private information was presented.The model breaks through institutional constraints through technological innovation, achieving a balance between improving data value and ensuring data security.Three sub-layers of the core system of secure multi-party computation in the proposed model, including the joint computation substructure layer, the secure relational algebra layer, and the basic operator layer of secure multi-party computation were mainly analyzed.Additionally, a general process for implementing the innovative model was presented, and the practical application of the innovative model was also discussed.The results of this study provide a new reference for promoting digital China construction and facilitating the flow of data resources.