A Survey of techniques for fine-grained web traffic identification and classification

After decades of rapid development, the scale and complexity of modern networks have far exceed our expectations. In many conditions, traditional traffic identification methods cannot meet the demand of modern networks. Recently, fine-grained network traffic identification has been proved to be an e...

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Published inMathematical biosciences and engineering : MBE Vol. 19; no. 3; pp. 2996 - 3021
Main Authors Gui, Xiaolin, Cao, Yuanlong, You, Ilsun, Ji, Lejun, Luo, Yong, Luo, Zhenzhen
Format Journal Article
LanguageEnglish
Published United States AIMS Press 01.01.2022
Subjects
fine-grained traffic identification
traffic classification
traffic identification
web traffic
web traffic
traffic identification
traffic classification
fine-grained traffic identification
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Abstract After decades of rapid development, the scale and complexity of modern networks have far exceed our expectations. In many conditions, traditional traffic identification methods cannot meet the demand of modern networks. Recently, fine-grained network traffic identification has been proved to be an effective solution for managing network resources. There is a massive increase in the use of fine-grained network traffic identification in the communications industry. In this article, we propose a comprehensive overview of fine-grained network traffic identification. Then, we conduct a detailed literature review on fine-grained network traffic identification from three perspectives: wired network, mobile network, and malware traffic identification. Finally, we also draw the conclusion on the challenges of fine-grained network traffic identification and future research prospects.
AbstractList After decades of rapid development, the scale and complexity of modern networks have far exceed our expectations. In many conditions, traditional traffic identification methods cannot meet the demand of modern networks. Recently, fine-grained network traffic identification has been proved to be an effective solution for managing network resources. There is a massive increase in the use of fine-grained network traffic identification in the communications industry. In this article, we propose a comprehensive overview of fine-grained network traffic identification. Then, we conduct a detailed literature review on fine-grained network traffic identification from three perspectives: wired network, mobile network, and malware traffic identification. Finally, we also draw the conclusion on the challenges of fine-grained network traffic identification and future research prospects.After decades of rapid development, the scale and complexity of modern networks have far exceed our expectations. In many conditions, traditional traffic identification methods cannot meet the demand of modern networks. Recently, fine-grained network traffic identification has been proved to be an effective solution for managing network resources. There is a massive increase in the use of fine-grained network traffic identification in the communications industry. In this article, we propose a comprehensive overview of fine-grained network traffic identification. Then, we conduct a detailed literature review on fine-grained network traffic identification from three perspectives: wired network, mobile network, and malware traffic identification. Finally, we also draw the conclusion on the challenges of fine-grained network traffic identification and future research prospects.
After decades of rapid development, the scale and complexity of modern networks have far exceed our expectations. In many conditions, traditional traffic identification methods cannot meet the demand of modern networks. Recently, fine-grained network traffic identification has been proved to be an effective solution for managing network resources. There is a massive increase in the use of fine-grained network traffic identification in the communications industry. In this article, we propose a comprehensive overview of fine-grained network traffic identification. Then, we conduct a detailed literature review on fine-grained network traffic identification from three perspectives: wired network, mobile network, and malware traffic identification. Finally, we also draw the conclusion on the challenges of fine-grained network traffic identification and future research prospects.
Author Ji, Lejun
Luo, Yong
Cao, Yuanlong
You, Ilsun
Gui, Xiaolin
Luo, Zhenzhen
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Department of Information Security Engineering, Soonchunhyang University, Asan 31538, South Korea
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traffic identification
traffic classification
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Snippet After decades of rapid development, the scale and complexity of modern networks have far exceed our expectations. In many conditions, traditional traffic...
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SubjectTerms fine-grained traffic identification
traffic classification
traffic identification
web traffic
Title A Survey of techniques for fine-grained web traffic identification and classification
URI https://www.ncbi.nlm.nih.gov/pubmed/35240817
https://www.proquest.com/docview/2636147659
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