Classification and Prediction of Network Abnormal Data Based on Machine Learning

被引：2
|
作者：
Ren, Bin [1 ,2 ]
Hu, Ming [2 ]
Yan, Hui [1 ,2 ]
Yu, Ping [1 ,2 ]
机构：
[1] Changchun Inst Technol, Sch Comp Technol & Engn, Changchun 130012, Peoples R China
[2] Jilin Prov Sci & Technol Innovat Ctr Phys Simulat, Changchun 130012, Peoples R China
来源：
2019 INTERNATIONAL CONFERENCE ON ROBOTS & INTELLIGENT SYSTEM (ICRIS 2019) | 2019年
关键词：
Machine Learning; Abnormal Data; Neural Network; Classification and Detection;
D O I：
10.1109/ICRIS.2019.00078
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Network abnormal data detection is the main method used for network security situational awareness. In order to reduce the false positives and false negatives of intrusion data, it is proposed to preprocess the data used for prediction by K-means method. In the data prediction, the method of feed forward neural network is adopted, and different loss functions are used to improve the accuracy of prediction and reduce the loss value, and obtain better experimental results.
引用
收藏
页码：273 / 276
页数：4
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