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In the process of the detection method of network attacks in campus network, with current algorithm, there are defects such as high demand for data and low detection rate for model. Therefore, a network attack detection method based on improved Hidden Markov Model algorithm is proposed. Structure and characteristics of the campus network is firstly analyzed. Based on the hidden Markov model, the learning of the normal school network behavior sample is then established. On this basis, the information entropy of information theory is introduced to measure the degree of dispersion of source IP addresses. According to the change of the initial stage of Hurst index and entropy threshold is adaptive set to detect the attacks so as to complete attack behavior detection. The experimental results show that the detection method based on the improved hidden Markov model has high accuracy and robustness.

The detection method of Network attacks in Campus Network