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The Scientific World JournalVolume 2014 2014, Article ID 374260, 7 pages

Research Article

College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang 050000, China

College of Information Technology, Hebei Normal University, Shijiazhuang 050000, China

The First Aeronautics College of PLAAF, Xinyang 464000, China

Received 8 April 2014; Accepted 6 May 2014; Published 28 May 2014

Academic Editor: Yuxin Mao

Copyright © 2014 Yanxue Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The biggest difficulty of hidden Markov model applied to multistep attack is the determination of observations. Now the research of the determination of observations is still lacking, and it shows a certain degree of subjectivity. In this regard, we integrate the attack intentions and hidden Markov model HMM and support a method to forecasting multistep attack based on hidden Markov model. Firstly, we train the existing hidden Markov models by the Baum-Welch algorithm of HMM. Then we recognize the alert belonging to attack scenarios with the Forward algorithm of HMM. Finally, we forecast the next possible attack sequence with the Viterbi algorithm of HMM. The results of simulation experiments show that the hidden Markov models which have been trained are better than the untrained in recognition and prediction.

Autor: Yanxue Zhang, Dongmei Zhao, and Jinxing Liu



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