Access Model of Web Users Based on Multi-chains Hidden Markov Models

K. Zheng, Yixian Yang, Xiujuan Wang, Shize Guo
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Abstract

How to distinguish abnormal access from normal ones is the key problem in Distribution Denial of service(DDoS) attack detection. This research aims at finding out the major difference between the abnormal access and the normal ones in application layer. To this end, the paper conducts modeling on Web users’ access behaviors based on hidden Markov model(HMM) with multiple chains and puts forward a method to identify abnormal access. Tests on simulation data indicate that this model can undo Web users access to a certain degree and discern the abnormal access well.
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基于多链隐马尔可夫模型的Web用户访问模型
如何区分异常访问和正常访问是分布式拒绝服务(DDoS)攻击检测中的关键问题。本研究旨在找出应用层异常访问与正常访问的主要区别。为此,本文基于多链隐马尔可夫模型(HMM)对Web用户的访问行为进行建模,并提出了一种异常访问识别方法。仿真数据测试表明,该模型能在一定程度上撤销Web用户的访问,并能很好地识别异常访问。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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