Importance Analysis of Traffic Statistics Information for VPN/NoN-VPN Classification 


Vol. 47,  No. 11, pp. 1768-1775, Nov.  2022
10.7840/kics.2022.47.11.1768


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  Abstract

With the rapid growth of the network environment, the usage of the Internet is increasing. In such a situation, efficient network operation of a network manager is required, and it is important for network users to accurately classify traffic in order to receive appropriate QoS. VPN is being adopted as one of the security methods of network communication. However, the malicious use of encryption is increasing and it is being used as a tool to evade firewalls. Accordingly, it is essential to classify VPNs and NoN-VPNs for efficient network operation. In this paper, we propose a method to classify VPN and NoN-VPN by combining traffic flow information and statistical items. When statistical information is used, classification accuracy of about 98% can be shown even by using only machine learning, and statistical information that plays an important role in classification among flow information and statistical items is analyzed.

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[IEEE Style]

M. Lee, J. Park, U. Baek, J. Choi, M. Kim, "Importance Analysis of Traffic Statistics Information for VPN/NoN-VPN Classification," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 11, pp. 1768-1775, 2022. DOI: 10.7840/kics.2022.47.11.1768.

[ACM Style]

Min-Seong Lee, Jee-Tae Park, Ui-Jun Baek, Jung-Woo Choi, and Myung-Sup Kim. 2022. Importance Analysis of Traffic Statistics Information for VPN/NoN-VPN Classification. The Journal of Korean Institute of Communications and Information Sciences, 47, 11, (2022), 1768-1775. DOI: 10.7840/kics.2022.47.11.1768.

[KICS Style]

Min-Seong Lee, Jee-Tae Park, Ui-Jun Baek, Jung-Woo Choi, Myung-Sup Kim, "Importance Analysis of Traffic Statistics Information for VPN/NoN-VPN Classification," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 11, pp. 1768-1775, 11. 2022. (https://doi.org/10.7840/kics.2022.47.11.1768)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880