利用RNN集成检测各种拒绝服务和分布式拒绝服务攻击

A. Islam, Tishna Sabrina
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引用次数: 16

摘要

拒绝服务(DoS)和分布式拒绝服务(DDoS)是众所周知的安全攻击,它们试图使计算机资源对目标用户不可用。在本文中,我讨论了一些众所周知的DoS和DDoS攻击。经验表明,在检测这些攻击时,人脑比数学计算更完美。因此,我提出了一种技术,结合人类大脑的代表,递归神经网络(RNN),以识别这些攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of various denial of service and Distributed Denial of Service attacks using RNN ensemble
Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) are widely known security attacks which attempt to make computer resources unavailable to its intended users. In this paper, I discuss some well known DoS and DDoS attacks. Experience shows that in the detection of these attacks human brain is more perfect than mathematical computation. Therefore, I propose a technique to incorporate the representative of human brain, Recurrent Neural Networks (RNN), to identify these attacks.
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