The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.
A survey of methods for encrypted traffic classification and analysis
Open accessAbstract
Summary: With the widespread use of encrypted data transport, network traffic encryption is becoming a standard nowadays. This presents a challenge for traffic measurement, especially for analysis and anomaly detection methods, which are dependent on the type of network traffic. In this paper, we survey existing approaches for classification and analysis of encrypted traffic. First, we describe the most widespread encryption protocols used throughout the Internet. We show that the initiation of an encrypted connection and the protocol structure give away much information for encrypted traffic classification and analysis. Then, we survey payload and feature‐based classification methods for encrypted traffic and categorize them using an established taxonomy. The advantage of some of described classification methods is the ability to recognize the encrypted application protocol in addition to the encryption protocol. Finally, we make a comprehensive comparison of the surveyed feature‐based classification methods and present their weaknesses and strengths. Copyright © 2015 John Wiley & Sons, Ltd.
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Cited by
Deep packet: a novel approach for encrypted traffic classification using deep learning
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End-to-end encrypted traffic classification with one-dimensional convolution neural networks
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FS-Net: A Flow Sequence Network For Encrypted Traffic Classification
Liu, C., He, L., Xiong, G., Cao, Z., & Li, Z. (2019) · IEEE INFOCOM 2019 - IEEE Conference on Computer Communications · doi:10.1109/infocom.2019.8737507 · Cited by 630
Machine Learning-Powered Encrypted Network Traffic Analysis: A Comprehensive Survey
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Ullah, S., Zheng, J., Din, N., Hussain, M. T., Ullah, F., & Yousaf, M. (2023) · Computer Science Review · doi:10.1016/j.cosrev.2022.100530 · Cited by 195
Metadata
- Authors
- Velan, P., Čermák, M., Čeleda, P., & Drašar, M.
- Venue
- International Journal of Network Management
- Publisher
- Wiley
- Published
- 2015-07-15
- Volume
- 25
- Issue
- 5
- Pages
- 355-374
- ISSN
- 1055-7148 (ISSN-L)
- 1099-1190
- OpenAlex
- W2613715541
- Cited by
- 377
- References
- 50
- FWCI
- 13.14
- Type
- journal article
- Language
- en
- Open access
- green
- Funders
- Ministry of the Interior of the Czech Republic (VF)
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