Power consumption data desensitization algorithm model construction method based on anonymization privacy technology

Abstract

The invention relates to a power consumption data desensitization algorithm model construction method based on an anonymization privacy technology. The method is characterized by comprising the following steps of 1, researching a data desensitization method in a multi-source heterogeneous big data environment; 2, analyzing and comparing the adaptability conditions of anonymization, data encryptionand differential privacy technologies in a power consumption information acquisition data environment; 3, constructing a power consumption data desensitization algorithm model based on anonymizationand differential privacy technologies; and step 4, researching and developing a power consumption data desensitization tool and carrying out trial point application. The invention discloses a power utilization data desensitization algorithm model construction method based on an anonymization privacy technology. A customizable power consumption data desensitization algorithm model is constructed; the desensitization requirements of different users can be accurately met, the convenience and safety of information sharing are considered, the privacy safety of sensitive data in use, release and sharing links in marketing and acquisition systems is guaranteed, and the leakage risk of mass power marketing data, power customer data and personal power consumption information of state grid companiesis effectively reduced.

Description

technical field [0001] The invention belongs to the field of electric power data processing, and relates to a model building method of an electricity data desensitization algorithm, in particular to a method for building a model of an electricity data desensitization algorithm based on an anonymization privacy technology. Background technique [0002] Power companies have a large amount of sensitive data such as power marketing data, power customer data, and personal power consumption information. These data have potential security risks of privacy leakage in the links of generation, transmission, storage, processing, and use and sharing. Therefore, a method for building an electricity data desensitization algorithm model based on anonymization privacy technology is designed to desensitize all kinds of sensitive data, so as to effectively protect the massive power marketing data, power customer data and personal consumption data in the State Grid Corporation system. Electron...

AI Technical Summary

Problems solved by technology

[0002] Power companies have a large amount of sensitive data such as power marketing data, power customer data, and personal power consumption information. These data have hidden security risks of privacy leakage in the links of generation, transmission, storage, processing, and use and sharing.

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