Learning from imbalanced data for encrypted traffic identification problem-Reference-Cited by-同舟云学术

Learning from imbalanced data for encrypted traffic identification problem

Published:2016-12-08 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Seventh Symposium on Information and Communication Technology
language:
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Author:

Vu Ly¹,Van Tra Dong²,Nguyen Quang Uy¹

Affiliation:

1. Le Quy Don University, Ha noi, Vietnam

2. Technical Economic College, Ho Chi Minh City, Vietnam

Funder

Viet Nam National Foundation for Science and Technology Development

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3011077.3011132

Reference20 articles.

1. Can encrypted traffic be identified without port numbers, ip addresses and payload inspection?;Alshammari R.;Elsevier,2010

2. Fast condensed nearest neighbor rule

3. C. Bacquet K. Gumus D. Tizer A. N. Zincir-Heywood and M. I. Heywood. A comparison of unsupervised learning techniques for encrypted traffic identification. 2010. C. Bacquet K. Gumus D. Tizer A. N. Zincir-Heywood and M. I. Heywood. A comparison of unsupervised learning techniques for encrypted traffic identification. 2010.

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