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http://dx.doi.org/10.3837/tiis.2014.03.007

An Integrated Method for Application-level Internet Traffic Classification  

Choi, Mi-Jung (Dept. of Computer Science, Kangwon National Univ.)
Park, Jun-Sang (Dept. of Computer and Information Science, Korea Univ., Sejong Campus)
Kim, Myung-Sup (Dept. of Computer and Information Science, Korea Univ., Sejong Campus)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.8, no.3, 2014 , pp. 838-856 More about this Journal
Abstract
Enhanced network speed and the appearance of various applications have recently resulted in the rapid increase of Internet users and the explosive growth of network traffic. Under this circumstance, Internet users are eager to receive reliable and Quality of Service (QoS)-guaranteed services. To provide reliable network services, network managers need to perform control measures involving dropping or blocking each traffic type. To manage a traffic type, it is necessary to rapidly measure and correctly analyze Internet traffic as well as classify network traffic according to applications. Such traffic classification result provides basic information for ensuring service-specific QoS. Several traffic classification methodologies have been introduced; however, there has been no favorable method in achieving optimal performance in terms of accuracy, completeness, and applicability in a real network environment. In this paper, we propose a method to classify Internet traffic as the first step to provide stable network services. We integrate the existing methodologies to compensate their weaknesses and to improve the overall accuracy and completeness of the classification. We prioritize the existing methodologies, which complement each other, in our integrated classification system.
Keywords
application-level traffic classification; signature-based classifier; behavior algorithm; correlation algorithm; integrated classification;
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Times Cited By KSCI : 2  (Citation Analysis)
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