A survey of methods for encrypted traffic classification and analysis
Обзор методов классификации и анализа зашифрованного трафика
2015-07-15
SCID: 54.1/m8wsftq3
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encrypted traffic analysisencrypted traffic classificationencryption protocolsfeature-based classificationpayload-based classification
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Abstract (AI)
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.
Key Findings
1
A comprehensive comparison shows distinct strengths and weaknesses among feature-based encrypted-traffic classification methods.
2
Encrypted traffic classification is important for traffic measurement, analysis, and anomaly detection because these tasks depend on traffic type.
3
Encrypted traffic remains classifiable because connection initiation patterns and protocol structures reveal substantial information despite payload encryption.
4
Some classification methods can identify the underlying encrypted application protocol in addition to the encryption protocol.
5
The survey organizes existing encrypted-traffic classification methods into payload-based and feature-based approaches using an established taxonomy.
Research Object
encrypted network traffic
Research Subject
classification and analysis methods, including protocol identification and comparative performance of payload- and feature-based approaches
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2015-07-15
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