文章基本信息

标题：Survey on Interference Disclosure System by Using Machine Learning in Software Defined Network
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作者：Elumalai J ; Bhuvaneshwari D ; Malathi R 等
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2018
卷号：7
期号：2
页码：1308
DOI：10.15680/IJIRSET.2018.0702048
出版社：S&S Publications
摘要：Software-Defined Networks (SDN) is an emerging area that promises to change the way we design,build, and operate network architecture. It tends to shift from traditional network architecture of proprietary based toopen and programmable network architecture. Security is one of the major issue in SDN. Wse propose a system thatsend data in alternate path if traffic occurs or connection closed in the current path.Machine learning algorithm canpredict the hindrance in the path and sends alert message to the client, then the client can change the route of the datain other shortest path. The data travelled path is stored in the MAC table for further references. The OTP message willsend to the user mail id whenever they login to prevent the intruder. Here the intruder cannot steal the data because thedata is in encrypted format, the only thing the intruder can do is either crash the data or change the data path. Theadvantage of the system is security and accuracy improved by using software defined network machine learningmethodologies.
关键词：Software-defined Network; Intrusion Detection System; Machine Learning