Analysis method for ensuring data privacy and service confidentiality

Abstract

The invention relates to the technical field of customer association relationship analysis, and discloses an analysis method for ensuring data privacy and service confidentiality, which comprises thefollowing steps: S1, extracting data to be analyzed, and placing the data in a two-dimensional table which defines a plurality of fields; s2, encrypting all data in the two-dimensional table by usinga hash algorithm; s3, splitting the encrypted data in the two-dimensional table, and performing mapping by utilizing a data association relationship to obtain a data association relationship graph; analyzing the data association relation graph by utilizing a graph calculation algorithm, and calculating and analyzing a result; S4, decrypting the result calculated and analyzed in the step S3 to obtain a final analysis result plaintext. On the premise of ensuring the data security, the technical provider can remotely help the data owner to analyze the data association relationship, the big data analysis cost is reduced, and the data privacy and the service confidentiality are improved.

Description

technical field [0001] The invention relates to the technical field of customer relationship analysis, in particular to an analysis method for ensuring data privacy and business confidentiality. Background technique [0002] In the process of analyzing customer data and big data, financial institutions often need to analyze the relationship between data. For example, someone A is a friend of B, and B is a friend of C. If A and C do not know each other, then there is a two-degree friendship relationship between A and C. When researching the customer's risk, we may need to find all of A's one-degree and two-degree friends, which involves some analysis methods for the relationship between customer data. We can build a graph (Graph) on the data and perform graph calculations ( Graph Computing) to achieve. In the practical application of customer data analysis, financial institutions often require technology companies to keep the data provided by the institution confidential. ...

AI Technical Summary

Problems solved by technology

However, in many cases, technology companies and financial institutions may not be located in the same city, requiring personnel to travel on site, resulting in problems such as high cost of big data analysis

Not only that, although the process of customer data analysis is completed within the financial institution, because technology companies have access to customer data in plain text and understand the specific business problems that the financial institution wants to solve, on-site big data analysis cannot be fully implemented. Guarantee the data privacy and data security of financial institution customers (for example, technicians may take pictures of the data displayed on the computer screen, and then send the pictures)

Images