网络应用流类别不平衡环境下的SSL加密应用流识别关键技术
通过深入研究网络类别不平衡的原因,选择SMOTE（synthetic minority over-sampling technique）过抽样方法对数据集进行预处理,并充分利用特征匹配高准确性的优点识别和分拣出SSL加密流,进而利用基于互信息最大化的聚类方法和SVM分类方法进一步识别SSL加密应用,这种混合方法有效地结合了静态特征匹配和机器学习方法的优点,达到识别分类方法在准确性和识别速度的均衡....
Saved in:
| Published in: | 电信科学 Vol. 31; no. 12; pp. 83 - 89 |
|---|---|
| Main Author: | |
| Format: | Journal Article |
| Language: | Chinese |
| Published: |
2015
|
| Subjects: | |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 通过深入研究网络类别不平衡的原因,选择SMOTE（synthetic minority over-sampling technique）过抽样方法对数据集进行预处理,并充分利用特征匹配高准确性的优点识别和分拣出SSL加密流,进而利用基于互信息最大化的聚类方法和SVM分类方法进一步识别SSL加密应用,这种混合方法有效地结合了静态特征匹配和机器学习方法的优点,达到识别分类方法在准确性和识别速度的均衡. |
|---|---|
| Bibliography: | traffic identification, traffic analysis, behavior characterization, behavior modeling, behavior pattern 11-2103/TN Through a in-depth study about the reason of network class imbalance, a method called SMOTE was chosen over the data set sampling preprocess, making full use of the advantages which is high accuracy of traffic model feature matching identification and sorting out the encrypted SSL flow, and then using the clustering method and the SVM based on mutual information classification method to further identify SSL encryption specific application, like HrP3PS/POPS etc. The hybrid method effectively combines the advantages of static feature matching and machine learning methods, to achieve the balance of classification method on accuracy and speed. Chen Xuejiao, Wang Pan, Liu Shidong （1. Nanjing College of Information Technology, Nanjing 210023, China; 2. Nanjing University of Posts and Telecommunications, Nanjing 210003, China; 3. State Grid Smart Grid Research Institute, Nanjing 210003, China） |
| ISSN: | 1000-0801 |