Approach to Forecasting Multi-step Attack Based on Fuzzy Hidden Markov Model

Zhang yanxue; Zhao Dongmei; Liu Jinxing
November 2013
Journal of Applied Sciences;2013, Vol. 13 Issue 22, p4955
Academic Journal
We integrate the approach of forecasting multi-step attack, the association rule, fuzzy evaluation and Hidden Markov Model (HMM) and support the method of forecasting multi-step attack based on fuzzy Hidden Markov Model. Firstly, we fuse raw alerts into super alert. Then we obtain the initial state matrix by the probability of the attack, determine the state transition matrix by the association rule and obtain the observation matrix by fuzzy evaluation. Finally, we recognize the alert belonging to attack scenarios with the Forward algorithm of HMM and forecast the next possible attack sequence with the Viterbi algorithm of HMM. Simulation experiments results verify the validity of the approach.


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