学习问题在异常入侵检测系统中的应用

The Second International Conference on Availability, Reliability and Security (ARES'07) Pub Date : 2007-04-10 DOI:10.1109/ARES.2007.35

Veselina G. Jecheva, E. Nikolova

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引用次数: 0

摘要

本文介绍了一种基于隐马尔可夫模型和BCJR解码算法的异常入侵检测方法。主要思想是使用BCJR解码算法结合基于梯度的HMM参数调整方法来区分用户活动的正常轨迹和异常轨迹。文中还介绍了仿真实验的一些结果

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An Application of Learning Problem in Anomaly-based Intrusion Detection Systems

The present paper introduces an approach to anomaly-based intrusion detection using the hidden Markov models (HMM) and the BCJR decoding algorithm. The main idea is to distinguish the normal traces of user activity from abnormal ones using the BCJR decoding algorithm applied in conjunction with HMM parameters adjustment using the gradient based method. Some results from the conducted simulation experiments are introduced as well

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The Second International Conference on Availability, Reliability and Security (ARES'07)

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