Research on Desensitization Algorithm of Power Consumption Data Based on Anonymity and Differential Privacy Technology
Bin Xu, Xiaobing Liang, Feng Zhai · IOP Conference Series Materials Science and Engineering · 2020
Abstract With the development of information technology, the problem of privacy disclosure has become increasingly prominent. State Grid Corporation has a large number of sensitive data such as power marketing data, power customer data, personal electricity information, which has disclosure dangers during the production, transmission, storage, processing and sharing stage. This paper mainly studies the desensitization algorithm model of power consumption data based on anonymity and differential privacy technology, builds a general algorithm model and then realizes data desensitization according to each application scenario. The evaluation and analysis results show that the scheme can effectively protect the massive power marketing data, power customer data and personal power information from invasion and disclosure.