Data Desensitization Method of Electricity Information
Shuai Yang, Kun-lun GAO, Ting Zhao, Jiang-qi CHEN · DEStech Transactions on Engineering and Technology Research · 2017
With the explosive growth of electricity information, its potential value and security problem is becoming more and more attractive. To ensure the safety and reliability of electricity data at different application levels, this paper proposes two kinds of data desensitization methods based on Fourier transform theory by studying the appropriate processing measurements, connotation and adjustable parameters. Specifically, recoverable and irreversible desensitization methods are proposed, which are used in the typical scene of electric data mining—load clustering. Experiments show that both types of methods can support clustering analysis effectively.