Small area purification and recognition of network intrusion signals based on the second-order matching filter detection

In order to improve the ability of intrusion detection and recognition. This paper proposes a method of small area purification and recognition of network intrusion signal based on second-order matched filter detection. In this method, the time-frequency analysis of network intrusion signal is carried out, and Hilbert Huang transform is used to decompose the time-delay scale of small-scale network intrusion signal, and then the spectrum feature is input into the second-order lattice matched filter to improve the signal resolution, and adaptive weighting method is used to adjust the filter tap coefficient to improve the detection and recognition ability. The simulation results show that the method can accurately recover two groups of component information of network intrusion signal: sinusoidal signal and sinusoidal frequency modulation signal. The recognition accuracy of network intrusion signal can reach 100%, which shows that the method has good signal purification performance.