A novel stochastic modeling method for network security situational awareness

Y. Liang, H.Q. Wang, H.B. Cai, Y. He
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引用次数: 7

Abstract

Hidden Markov model (HMM) is used to model network security situational awareness (NSA). Distribution of abnormal behaviors in networked system and operational states of key network services are abstracted by Markov chains, modeling objects of the HMM's dual stochastic processes are set up, and classic Baum-Welch algorithm is used to estimate the parameters of the established stochastic mathematical model, then the stochastic modeling for network security situational awareness based upon HMM is realized. The simulation experimental results in LAN show that the model can effectively analyze and validate network security situation, and it is a novel attempt in achieving network security situational awareness, which prompts the development of theoretical researches in the field of NSA at a certain degree.
一种新的网络安全态势感知随机建模方法
隐马尔可夫模型(HMM)用于网络安全态势感知模型。利用马尔可夫链抽象网络系统异常行为的分布和关键网络服务的运行状态,建立HMM双随机过程的建模对象,利用经典的Baum-Welch算法对所建立的随机数学模型进行参数估计,实现了基于HMM的网络安全态势感知的随机建模。局域网中的仿真实验结果表明,该模型能够有效地分析和验证网络安全态势,是实现网络安全态势感知的一种新颖尝试,在一定程度上促进了NSA领域理论研究的发展。
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