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Behavior Signature for Fine-grained Traffic Identification |
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PP: 523-534 |
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Author(s) |
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Sung-Ho Yoon,
Jun-Sang Park,
Myung-Sup Kim,
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Abstract |
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| With the rapid development of the Internet and a vigorous emergence of new applications, traffic identification has become
a key issue for efficient network management. Although various methods have been proposed, there are still several limitations to
achieving fine-grained and application-level traffic identification. In this paper, we propose a new signature model called a behavior
signature for Internet traffic identification that utilizes the inter-flow relation of application traffic. The proposed behavior signature
is a unique traffic behavior pattern appearing in the first few packets of plural traffic flows when a specific function is conducted
by an application with a combination of various optional traffic features. This is in contrast to other existing signature models that
usually focus on a singular packet or flow for feature extraction and traffic identification. We proved the feasibility and applicability
of the proposed behavior signature by developing an extraction and identification algorithm and by conducting experiments on several
popular applications. |
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