Research on Classification and Desensitization Strategies of Sensitive Educational Data

In the era of digital intelligence, data is a key element in promoting social and economic development. Educational data, as a vital component of data, not only supports teaching and learning but also contains much sensitive information. How to effectively categorize and protect sensitive data has become an urgent issue in educational data security. This paper systematically researches and constructs a multi-dimensional classification framework for sensitive educational data, and discusses its security protection strategy from the aspects of identification and desensitization, aiming to provide new ideas for the security management of sensitive educational data and to help the construction of an educational data security ecosystem in the era of digital intelligence.