| Title | Intelligent Data Security Threat Discovery Model Based on Grid Data |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Chen, Lin, Qiu, Huijun, Kuang, Xiaoyun, Xu, Aidong, Yang, Yiwei |
| Conference Name | 2021 6th International Conference on Image, Vision and Computing (ICIVC) |
| Date Published | jul |
| Keywords | compositionality, Data analysis, Data models, Data security, intelligent data, migration learning, process control, pubcrawl, reinforcement learning, resilience, Resiliency, Scalability, security, Smart grid, Training, transfer learning |
| Abstract | With the rapid construction and popularization of smart grid, the security of data in smart grid has become the basis for the safe and stable operation of smart grid. This paper proposes a data security threat discovery model for smart grid. Based on the prediction data analysis method, combined with migration learning technology, it analyzes different data, uses data matching process to classify the losses, and accurately predicts the analysis results, finds the security risks in the data, and prevents the illegal acquisition of data. The reinforcement learning and training process of this method distinguish the effective authentication and illegal access to data. |
| DOI | 10.1109/ICIVC52351.2021.9526924 |
| Citation Key | chen_intelligent_2021 |
Intelligent Data Security Threat Discovery Model Based on Grid Data