Intelligent detection method on network malicious traffic based on sample enhancement |
| |
Authors: | Tieming CHEN Chengqiang JIN Mingqi LYU Tiantian ZHU |
| |
Affiliation: | School of Computer Science and Technology,Zhejiang University of Technology,Hangzhou 310023,China |
| |
Abstract: | To address the problem that the existing methods of network traffic anomaly detection not only need a large number of training sets,but also have poor generalization ability,an intelligent detection method on network malicious traffic based on sample enhancement was proposed.The key words were extracted from the training set and the sample of the training set was enhanced based on the strategy of key word avoidance,and the ability for the method to extract the text features from the training set was improved.The experimental results show that,the accuracy of network traffic anomaly detection model and cross dataset can be significantly improved by small training set.Compared with other methods,the proposed method can reduce the computational complexity and achieve better detection ability. |
| |
Keywords: | sample enhancement anomaly detection traffic detection machine learning |
|
| 点击此处可从《通信学报》浏览原始摘要信息 |
|
点击此处可从《通信学报》下载全文 |
|