Abnormal State Warning System of Network Security Management based on KD Tree and KNN

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With the development of the times, students' network security is gradually threatened, so it is necessary to use a student network security management abnormal state warning system to manage student network security issues. However, the current student network security management abnormal state warning system is still not perfect, so new technologies are used to improve. This article studied a student network security management anomaly warning system based on KD tree and KNN algorithm, aiming to improve student network security by using KD tree and KNN algorithm. This article tested through experiments that after using KD tree and KNN algorithm, the highest number of student network security accidents was 12, and the lowest was 7. However, the traditional algorithm had a maximum of 35 and a minimum of 28 student network security accidents. From this experimental result, it can be seen that using KD tree and KNN algorithm can effectively reduce student network security accidents. This proved that the KD tree and KNN algorithm can achieve good results in the abnormal state warning system for student network security management.