Research on Privacy Protection of Power Users Based on Big Data Desensitization Technology
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Xin Jiang, Ran Chen, Dongyin Chen, Yuxiang Cai, Jia Liu, Jiemin Zhang
With the advent of the Internet and big data era, the value of data has become more and more significant, and its role in various fields has become more and more important. It has also spawned a new research field, namely data privacy and security. Grid companies have collected and stored massive amounts of electricity customer data, and it has become particularly urgent to solve the problem of how to ensure the privacy and security of customer data during use. By analyzing the characteristics and application scenarios of power customer data, we propose a power customer data privacy protection system construction plan covering business scenario classification, privacy classification, protection strategy and protection method library, and build an active privacy protection mechanism for power customer data to achieve Active recommendation of power customer data privacy protection strategies and technical methods. The actual case shows that the established power customer data privacy protection system has good practicability.
Big data; Power user information; Privacy protection