Semi-Supervised Malware Traffic Classification Via Consistency Regularization and Pseudo-Labeling-Reference-Cited by-同舟云学术

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Semi-Supervised Malware Traffic Classification Via Consistency Regularization and Pseudo-Labeling

Published:2023-10-20 Issue: Volume:24 Page:1008-1012
ISSN:
Container-title:2023 IEEE 23rd International Conference on Communication Technology (ICCT)
language:
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Author:

Jiao Qianlong¹,Zhang Xixi¹,Zhang Weijie²,Miao Fucheng³,Ohtsuki Tomoaki⁴,Adebisi Bamidele⁵,Wang Yu¹,Gui Guan¹

Affiliation:

1. College of Telecommunications and Information Engineering, NJUPT,Nanjing,China

2. Reading Academy, Nanjing University of Information Science and Technology,Nanjing,China

3. Nanjing Great Information Technology Co. Ltd,Nanjing,China

4. Keio University,Department of Information and Computer Science,Yokohama,Japan

5. Manchester Metropolitan University,Faculty of Science and Engineering,Manchester,United Kingdom

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10419380/10419200/10419749.pdf?arnumber=10419749

Reference20 articles.

1. Data-Driven Cyber Security in Perspective—Intelligent Traffic Analysis

2. MalDIST: From Encrypted Traffic Classification to Malware Traffic Detection and Classification

3. Efficient application identification and the temporal and spatial stability of classification schema

4. Accurate, scalable in-network identification of p2p traffic using application signatures

5. A survey of techniques for internet traffic classification using machine learning

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