Electric power big data desensitization method applied to privacy protection

• Main Authors: CHEN LONG, WANG YAJUAN, SUN LINTAN, LYU JINGXIAN, HAN WEI
• Format: Patent
• Language: Chinese; English
• Published: 10.04.2020
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention relates to an electric power big data desensitization method applied to privacy protection. The method comprises the following steps: step 1, collecting and arranging sensitive information in each database to form a source data table; 2, clustering the data in the data table T; compared with the prior art, the method has the advantages that on one hand, before data generalization, aclassification attribute is firstly determined to primarily classify a data table, so that the calculation complexity is reduced; on the other hand, when the distance between the data is calculated, the proportion of the attribute value in distance measurement is determined according to the variance of the current attribute value, so that clustering is more reasonable, the generalization degree isreduced as much as possible, and the data loss amount is reduced. 本发明涉及一种应用于隐私保护的电力大数据脱敏方法。包括以下步骤：步骤1：对各个数据库中的敏感信息进行收集和整理，形成源数据表；步骤2：对数据表T中的数据进行聚类；本发明相对于现有技术的优点在于：一方面对数据泛化前，先确定一种分类型属性对数据表初分类，以减少计算复杂度；另一方面在计算数据间距离时，根据当前属性值的方差确