Abstract:The traditional machine-learning-based network intrusion detection method can only detect the known intrusion behavior and has the disadvantages of high false alarm rate and poor timeliness when detecting unknown intrusion behavior. In this study, a new seismic information network intrusion detection method based on the chaos algorithm is proposed. First, the candidate seismic information network feature-chaos variable mapping model is created to enable the transformation between variables, and the chaos variable iterative evolution algorithm is used to select seismic information network features. Then, the support vector machine is used to learn optimal features. Finally, to improve the detection accuracy of seismic information network intrusion, the Cauchy bee colony algorithm is adopted to optimize the parameters of the support vector machine, and the optimization model of network intrusion detection is established. The simulation experiment results show that the seismic information network intrusion detection method based on the chaos algorithm can effectively implement intrusion detection with high detection rate and low false alarm rate, thus having high application advantage.