کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
447365 1443229 2008 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Semi-supervised internet network traffic classification using a Gaussian mixture model
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر شبکه های کامپیوتری و ارتباطات
پیش نمایش صفحه اول مقاله
Semi-supervised internet network traffic classification using a Gaussian mixture model
چکیده انگلیسی

With a dramatic increase in the number and variety of applications running over the internet, it is very important to be capable of dynamically identifying and classifying flows/traffic according to their network applications. Meanwhile, internet application classification is fundamental to numerous network activities. In this paper, we present a novel methodology for identifying different internet applications. The major contributions are: (1) we propose a Gaussian mixture model (GMM)-based semi-supervised classification system to identify different internet applications; (2) we achieve an optimum configuration for the GMM-based semi-supervised classification system. The effectiveness of these proposed approaches is demonstrated through experimental results.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: AEU - International Journal of Electronics and Communications - Volume 62, Issue 7, 1 August 2008, Pages 557–564
نویسندگان
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