Design And Implementation Of Data Masking System For Telecom Operators

With the rapid development of the Internet and the era of big data,the growth and utilization of data has reached a new height,and the value of data has been valued by people.With the help of big data,telecom operators have greatly improved their understanding of users,product improvement and profitability through data mining and analysis.Telecom operators have a large amount of user data,including personal identity,social relations,geographic location,credit status,and address book.However,the leakage of sensitive data caused by the use of these data often involves a large amount of customer sensitive data,which will cause serious damage to customer privacy,corporate interests and reputation,which has also become an increasingly serious problem in the field of information security.The common data masking methods may damage the value of the data itself,which puts forward requirements for the research of data masking algorithms.Therefore,how to achieve a balance between data availability and data privacy has become a problem that telecom operators must face and solve today.This article focuses on the research on the use of sensitive data security masking of telecom operators.The main work completed is as follows:1.Aiming at different scenarios where telecom operators use data,a dynamic / static masking combined data masking technology solution is designed to cope with different usage scenarios such as data analysis,sharing,development and testing.2.This paper studies the masking of numeric data,and the masking scheme implemented on the existing privacy protection scheme achieves the effect of retaining the statistical characteristics of the data.It satisfies the need for numerical data to provide value for data analysis under the premise of masking.3.This paper designs and implements a data masking system.The system is mainly divided into five parts,namely: data source management,masking strategy management,static data masking,dynamic data masking,and role authority management.The data source supports mainstream databases,including My SQL,Oracle,and SQL Server.