An Encrypted Traffic Identification Scheme Based on the Multilevel Structure and Variational Automatic Encoder
Autor: | Huaifeng Shi, Junjun Xing, Zhongjun Sun, Jiangtao Zhai, Mingqian Wang |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Science (General)
Article Subject Computer Networks and Communications Computer science business.industry Monte Carlo method Decision tree Mutual information Encryption Random forest Q1-390 T1-995 Entropy (information theory) business Algorithm Encoder Technology (General) Information Systems Curse of dimensionality |
Zdroj: | Security and Communication Networks, Vol 2020 (2020) |
ISSN: | 1939-0114 |
DOI: | 10.1155/2020/8863169 |
Popis: | With the rapid growth of the encrypted network traffic, the identification to it becomes a hot topic in information security. Since the existing methods have difficulties in identifying the application which the encrypted traffic belongs to, a new encrypted traffic identification scheme is proposed in this paper. The proposed scheme has two levels. In the first level, the entropy and estimation of Monte Carlo π value as features are used to identify the encrypted traffic by C4.5 decision tree. In the second level, the application types are distinguished from the encrypted traffic selected above. First, the variational automatic encoder is used to extract the layer features, which is combined with the frequently-used stream features. Meanwhile, the mutual information is used to reduce the dimensionality of the combination features. Finally, the random forest classifier is used to obtain the optimal result. Compared with the existing methods, the experimental results show that the proposed scheme not only has faster convergence speed but also achieves better performance in the recognition accuracy, recall rate, and F1-Measure, which is higher than 97%. |
Databáze: | OpenAIRE |
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