Title :
A Survey of Application-Level Protocol Identification Based on Machine Learning
Author :
Amei, Wu ; Huailin, Dong ; Qingfeng, Wu ; Ling, Lin
Author_Institution :
Software Sch., Xiamen Univ., Xiamen, China
Abstract :
Application-level protocol identification has attracted great interests in academia and become a relatively independent research realm. With the rapid development of Internet and the protocols complicated day by day, the traditional port-based application-level protocol identification algorithms become inaccurate. Machine learning is a hot research in the hour. Many researchers have taken the method into consideration in application protocol recognition. The high correct rate and wide applicability make it promising. In the paper, some basic conceptions of protocol identification are introduced and some important algorithms of machine learning used in application-level protocol identification are summarized in three main way. The applicability is summarized by comparison. In the end, some disadvantages in the method and future research directions are posed.
Keywords :
Internet; learning (artificial intelligence); protocols; Internet; application protocol recognition; machine learning; port-based application-level protocol identification; Accuracy; Bayesian methods; Classification algorithms; Internet; Machine learning; Machine learning algorithms; Protocols; algorithm; application-level protocol identification; machine learning;
Conference_Titel :
Information Management, Innovation Management and Industrial Engineering (ICIII), 2011 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-61284-450-3
DOI :
10.1109/ICIII.2011.331