| Title | Research on Intelligent Recognition and Tracking Technology of Sensitive Data for Electric Power Big Data |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Yang, Ruxia, Gao, Xianzhou, Gao, Peng |
| Conference Name | 2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) |
| Keywords | Automation, Big Data, classification and grading, Companies, compositionality, Data security, electric power big data, intelligent data, intelligent identification, Mechatronics, Power measurement, Probabilistic logic, pubcrawl, resilience, Resiliency, Scalability, security, tracking technology |
| Abstract | Current power sensitive data security protection adopts classification and grading protection. Company classification and grading are mainly in formulating specifications. Data classification and grading processing is carried out manually, which is heavy and time-consuming, while traditional data identification mainly relies on rules for data identification, the level of automation and intelligence is low, and there are many problems in recognition accuracy. Data classification and classification is the basis of data security protection. Sensitive data identification is the key to data classification and classification, and it is also the first step to achieve accurate data security protection. This paper proposes an intelligent identification and tracking technology of sensitive data for electric power big data, which can improve the ability of data classification and classification, help the realization of data classification and classification, and provide support for the accurate implementation of data security capabilities. |
| DOI | 10.1109/ICMTMA52658.2021.00057 |
| Citation Key | yang_research_2021 |
Research on Intelligent Recognition and Tracking Technology of Sensitive Data for Electric Power Big Data