VPN Encrypted Traffic classification using XGBoost
Journal: International Journal of Emerging Trends in Engineering Research (IJETER) (Vol.9, No. 7)Publication Date: 2021-07-07
Authors : Sami Smadi Omar Almomani Adel Mohammad Mohammad Alauthman Adeeb Saaidah;
Page : 960-966
Keywords : VPN; XGBoost; Encrypted traffic; ensemble learning; Network traffic classification.;
Abstract
Classification network traffic are becoming ever more relevant in understanding and addressing security issues inInternet applications. Virtual Private Networks (VPNs) have become one famous communication forms on the Internet. In this study, a new model for traffic classification into VPN or non-VPN is proposed. XGBoost algorithm is used to rank features and to build the classification model. The proposed model overwhelmed other classification algorithms. The proposed model achieved 91.6% accuracy which is the highest registered accuracy for the selected dataset. To illustrate the merit of the proposed model, a comparison was made with sixteen different classification algorithms
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Last modified: 2021-07-08 21:57:28