A novel approach for classification of Tor and non-Tor traffic using efficient feature selection methods-Reference-Cited by-同舟云学术

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A novel approach for classification of Tor and non-Tor traffic using efficient feature selection methods

Published:2024-09 Issue: Volume:249 Page:123544
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Gudla Raju^ORCID,Vollala Satyanarayana^ORCID,K.G. Srinivasa^ORCID,Amin Ruhul^ORCID

Publisher

Elsevier BV

Reference28 articles.

1. A comparative analysis of gradient boosting algorithms;Bentéjac;Artificial Intelligence Review,2021

2. A big data-enabled hierarchical framework for traffic classification;Bovenzi;IEEE Transactions on Network Science and Engineering,2020

3. SMOTE: synthetic minority over-sampling technique;Chawla;Journal of Artificial Intelligence Research,2002

4. Tor traffic analysis and detection via machine learning techniques;Cuzzocrea,2017

5. Identifying Tor anonymous traffic based on gravitational clustering analysis;Deng,2017

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