A fraudulent data sharing method, system and medium

Abstract

The present disclosure relates to a fraud-related data sharing method, system and medium. The method includes: step S1, receiving in parallel the fraud-related data uploaded by the first user via multiple nodes in real time; step S2, analyzing the fraud-related data, and performing an analysis on the fraud-related data based on the metadata of the fraud-related data Store; step S3, receive the query request of the second user in parallel in real time via the multiple nodes, and find the fraud-related data corresponding to the query request based on the query request; and step S4, according to the query request corresponding to the Metadata of fraudulent data, credit rating of the second user, and send fraudulent data meeting predetermined conditions to the second user; wherein, both the first user and the second user are authenticated users, and the The metadata includes the privacy level and encryption level of the fraud-related data, and the query request includes the 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.

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