A comparison of three machine learning techniques for encrypted network traffic analysis

DJ Arndt, AN Zincir-Heywood - 2011 IEEE symposium on …, 2011 - ieeexplore.ieee.org
This work evaluates three methods for encrypted traffic analysis without using the IP
addresses, port number, and payload information. To this end, binary identification of SSH …

[PDF][PDF] A Comparison of Three Machine Learning Techniques for Encrypted Network Traffic Analysis

DJ Arndt - scholar.archive.org
Ahstract-This work evaluates three methods for encrypted traffic analysis without using the IP
addresses, port number, and payload information. To this end, binary identification of SSH …

A Comparison of three machine learning techniques for encrypted network traffic analysis

DJ Arndt, AN Zincir-Heywood - … on Computational Intelligence for Security and … - infona.pl
This work evaluates three methods for encrypted traffic analysis without using the IP
addresses, port number, and payload information. To this end, binary identification of SSH …

[PDF][PDF] A Comparison of Three Machine Learning Techniques for Encrypted Network Traffic Analysis

DJ Arndt - Citeseer
Ahstract-This work evaluates three methods for encrypted traffic analysis without using the IP
addresses, port number, and payload information. To this end, binary identification of SSH …

[引用][C] A Comparison of three machine learning techniques for encrypted network traffic analysis

DJ Arndt, AN Zincir-Heywood - 2011 IEEE Symposium on Computational …, 2011 - cir.nii.ac.jp
A Comparison of three machine learning techniques for encrypted network traffic analysis |
CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索フォームへ …