基于水印与属性筛选的用电数据泄露溯源方法

计算机与现代化 ›› 2022, Vol. 0 ›› Issue (03): 37-42.

基于水印与属性筛选的用电数据泄露溯源方法

(国网江苏省电力有限公司营销服务中心,江苏南京210036)

出版日期:2022-04-29 发布日期:2022-04-29
作者简介:单超(1991—),男,河南开封人,工程师,硕士,研究方向:数据隐私保护,信息系统安全,E-mail: 1029121831@qq.com; 邹云峰(1977—),男,江西丰城人,高级工程师,硕士,研究方向:信息系统安全,大数据技术。
基金资助:
国网江苏省电力有限公司科技资助项目(J2020007)

Source Traceability Method for Power Consumption Data Leakage Based on Watermark and Attribute Screening

(Marketing Service Center, State Grid Jiangsu Electric Power Co.,LTD., Nanjing 210036, China）

Online:2022-04-29 Published:2022-04-29

摘要/Abstract

摘要： 用电数据涉及客户隐私，在分发共享过程中存在泄露风险，数字水印是实现泄露溯源追责的有效手段。而水印植入将导致数据偏移，影响数据分析可用性，且部分数据泄漏时溯源效果不够理想。本文提出一种基于子水印和属性筛选的用电数据泄露溯源算法WRTA，该方法通过利用信息增益率和基尼系数计算数据属性的重要程度，通过密钥和主键随机选择非重要属性来构建子水印，并且兼顾数据分析可用性和安全性，实现部分数据泄露的溯源。

关键词: 用电数据, 数据泄露溯源, 信息增益, 子水印

Abstract: Electricity consumption data involves customer’s privacy, and during the distribution and sharing process, it has the risk of unauthorized outgoing. Digital watermarking is an effective technology to realize leak traceability and hold them accountable. The implantation of watermarks will cause data offset and affect the usability of data analysis and the traceability effect is not good enough when some part of the data is leaked. In view of the above problems, this paper proposes an electricity data traceability algorithm WRTA based on sub-watermark and attribute filtering, which uses information gain rate and Gini coefficient to measure the influence of attributes on maintaining classification availability, and randomly selects non-important attributes through key and primary key to construct sub-watermarks. The algorithm can provide the availability and security of data analysis and realize the traceability of partial data leakage.

Key words: power consumption data, traceability of data leakage, information gain, sub-watermark

单超, 邹云峰. 基于水印与属性筛选的用电数据泄露溯源方法[J]. 计算机与现代化, 2022, 0(03): 37-42.

SHAN Chao, ZOU Yun-feng. Source Traceability Method for Power Consumption Data Leakage Based on Watermark and Attribute Screening[J]. Computer and Modernization, 2022, 0(03): 37-42.

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