DocumentCode :
650342
Title :
Early recognition of Internet service flow
Author :
Chang Huijun ; Shan Hong ; Zhu Hong
Author_Institution :
Electron. Eng. Instn. of PLA, Hefei, China
fYear :
2013
fDate :
16-18 May 2013
Firstpage :
464
Lastpage :
468
Abstract :
Early service flow recognition is required in both network management and intrusion detection systems. However, there exists some deficiency in existing machine learning methods when used in time or accuracy critical conditions. We put forward an early recognition method of Internet service flow and verify it by multiple experiment sets. As simulation results show, based on the packet lengths and the packet intervals of the first N packets, the method, utilizing improved k nearest neighbors (KNN) algorithm, can effectively identify the unknown service flow in the network.
Keywords :
Internet; computer network management; learning (artificial intelligence); security of data; support vector machines; Internet service flow; KNN; early service flow recognition; intrusion detection systems; k nearest neighbors algorithm; machine learning; network management; packet intervals; packet lengths; k nearest neighbor algorithm; packet interval; packet size; support vector machine; the decision tree classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless and Optical Communication Conference (WOCC), 2013 22nd
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-5697-8
Type :
conf
DOI :
10.1109/WOCC.2013.6676412
Filename :
6676412
Link To Document :
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