文章基本信息

标题：An Analysis of Machine Learning Depend on Q-MIND for Defencing The Distributed Denial of Service Attack on Software Defined Network
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作者：M. Sakthivel ; S. Sivanantham ; R. Kamalraj 等
期刊名称：International Journal of Early Childhood Special Education
电子版ISSN：1308-5581
出版年度：2022
卷号：14
期号：5
页码：3769-3776
DOI：10.9756/INTJECSE/V14I5.424
语种：English
出版社：International Journal of Early Childhood Special Education
摘要：A flexible and scalable network control was enabled in the Software Define Networking. It introduces unprotected network which can easily exploits by attackers. Especially, Distributed Denial of service attacks or low rate products are attracting researchers recently due to their detecting challenges. This research proposes novel machine learning depend on defence structure named Q-MIND which is used to mitigate and detect stealthy Distributed Denial of Service attacks in Software Denied Network. At first, everyone should examine the adversary design of stealthy Distributed Denial of Service attacks and negligence in Software Defined Network. And next narrates and examines the detection process which uses a RL approach depend on Q-MIND to maximize the performance of detection. And at last, outlines the whole Q-MIND defence structure should incorporate the policy of optimal derived from the agent of Q-Learning to defeat the Distributed Denial of Service attacks in Software Denied Network.
关键词：QMIND;SDN;distributed denial of service attack;RL;Q-Learning;networks