Deep Learning for Encrypted Traffic Classification: An Overview
نویسندگان
چکیده
منابع مشابه
Classification of encrypted traffic for applications based on statistical features
Traffic classification plays an important role in many aspects of network management such as identifying type of the transferred data, detection of malware applications, applying policies to restrict network accesses and so on. Basic methods in this field were using some obvious traffic features like port number and protocol type to classify the traffic type. However, recent changes in applicat...
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Network traffic classification has become significantly important with rapid growth of current Internet network and online applications. There have been numerous studies on this topic which have led to many different approaches. Most of these approaches use predefined features extracted by an expert in order to classify network traffic. In contrast, in this study, we propose a deep learning bas...
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Network traffic classification can be used to identify different applications and protocols that exist in a network. Actions such as monitoring, discovery, control and optimization can be performed by using classified network traffic. The overall goal of network traffic classification is improving the network performance. Once the packets are classified as belonging to a particular application,...
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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 w...
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ژورنال
عنوان ژورنال: IEEE Communications Magazine
سال: 2019
ISSN: 0163-6804,1558-1896
DOI: 10.1109/mcom.2019.1800819