能源大数据中心数据脱敏关键技术研究

Research on the Key Technology of Data Desensitization in the Energy Big Data Center

针对电网环境安全性较差引起的敏感数据易泄露、窃取等问题,提出一种能源大数据中心的数据脱敏关键技术。利用敏感数据样本的特征及属性,赋予所有样本同等支持度阈值,并计算数据间的隶属关系,通过关系参数对全部数据集实现敏感度划分,完成脱敏区间的建立。在此区间内计算同一背景属性下敏感数据与正常数据的重构概率,实行重构转换,完成数据的脱敏。实验结果证明技术对中心大数据脱敏的精准度较高、速度较快,且整体耗用较少。

In view of the problems of sensitive data leakage and stealing caused by the poor security of power grid environment,a key technology of data desensitization in big data center of energy is proposed.The sensitivity of all data sets is divided by the relationship parameters,and the desensitization interval is established.In this interval,the reconstruction probability of sensitive data and normal data is calculated under the same background attribute,and the reconstruction transformation is carried out to complete the desensitization of data.The experimental results show that the technology has high precision and speed for desensitization of central big data,and the overall consumption is less.