Intrusion detection method of a wireless communication network based on an improved hidden Markov model
The traditional intrusion detection methods are susceptible to the complexity of the network environment and the change of data flow characteristics,resulting in poor effect.In this paper,we propose an intrusion detection method of wireless communication networks based on an improved hidden Markov model.An abnormal state transition probability matrix and dy-namic threshold strategies are introduced to improve the accuracy and robustness of intrusion de-tection.In addition,this paper also proposes the method of grouping and progressive compres-sion for the computational complexity of the existing models when dealing with a large amount of data,to effectively improve the detection efficiency.According to the experimental results,the proposed method has a good intrusion detection effect in the wireless communication net-work,and can effectively identify malicious attacks and reduce the false positive rate.
network environmentintrusion detectionhidden Markov model and improve-ment method
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