Research on Grid Multi-Source Survey Data Sharing Algorithm for Cross-Professional and Cross-Departmental Operations Collaboration

This paper addresses the problem of multi-source survey data sharing in power system engineering by proposing two improved methods: a survey data sharing method combined with differential privacy and a permission change method based on attribute encryption. The survey data sharing method integrated with differential privacy achieves effective cross-professional and cross-departmental data sharing while ensuring data security by introducing multi-discriminator architecture and dynamic noise adjustment. To reduce the computational and communication overhead when user permissions change during survey data sharing, the attribute encryption-based permission change method supports dynamic changes in user permissions. The effectiveness of the proposed methods has been validated through targeted experiments in different scenarios. The work in this thesis provides a new solution for dynamic sharing of survey data in power network engineering. It contributes to the digital transformation of power network projects.