基于敏感性分级的教育数据可信存储模型研究OA

[Objective]Addressing the current issue of a lack of unified classification and grading stan-dards for educational data,which leads to difficulties in data security governance due to the ab-sence of standardized classification and grading management within the industry,this paper es-tablishes rules for the classification and grading of educational data and proposes a trusted stor-age model for educational data based on sensitivity grading.[Methods]Firstly,the"blockchain+HDFS"collaborative on-chain and off-chain storage approach was employed to alleviate blockchain storage bottlenecks while ensuring the security and efficiency of data storage.Secondly,a multi-chan-nel hierarchical storage structure was constructed to achieve isolated storage of sensitive data,effectively safe-guarding the security and credibility of such data.Finally,the deployment of smart contracts enabled automated and differentiated storage management of data,providing higher-level protection measures for sensitive data.[Results]Experimental results demonstrate that this model achieves good storage efficiency while ensuring se-cure data storage.Compared to traditional blockchain storage architectures,this solution reduces storage over-head by 31%,reduces time overhead by 98%,and also significantly reduces resource overhead.[Conclusions]It meets the storage requirements for large-scale educational data and enhances the privacy protection of sensitive educational data.