Fraud-related data sharing method and system and medium

Abstract

The invention relates to a fraud-related data sharing method and system and a medium. The method comprises the following steps: S1, receiving fraud-related data uploaded by a first user in parallel in real time through multiple nodes; S2, analyzing the fraud-related data, and storing the fraud-related data based on metadata of the fraud-related data; S3, receiving a query request of a second user in parallel in real time through the multiple nodes, and searching fraud-related data corresponding to the query request based on the query request; and S4, sending fraud-related data satisfying a predetermined condition to the second user according to metadata of the fraud-related data corresponding to the query request and the credit rating of the second user, wherein the first user and the second user are both authenticated users, the metadata comprises a privacy level and an encryption level of the fraud-related data, and the query request comprises identity information of the second user.

Description

technical field [0001] The present disclosure relates to the field of data sharing, and more specifically, to a fraud-related data sharing method, system and medium. Background technique [0002] At present, telecom network fraud is increasingly shifting to the Internet side, but the current prevention and governance models of the telecom and Internet industries remain relatively independent. Fraudsters have integrated the application of mobile Internet, artificial intelligence and other technical means, and adopted fraud methods such as high confrontation, strong concealment, and fast transfer to form fraudulent networks across borders, making prevention and governance increasingly difficult. In order to improve the governance system and enhance the effectiveness of governance, artificial intelligence and big data technologies are comprehensively used to break through the bottleneck of data circulation in the telecommunications and Internet industries. The big data anti-fra...

AI Technical Summary

Problems solved by technology

[0007] However, existing solutions are mainly designed for sharing and exchanging systems based on data characteristics in their respective fields, such as Internet of Things data, agricultural data, etc., or shared data platforms using blockchain technology, but they are not suitable for fraudulent data sharing and exchange. Requirements, such as data security, privacy protection, heterogeneous real-time concurrent input, content availability, personalized sharing and exchange methods, etc.

Images