An Immune-based Combination Predication Model for network security situation

Due to the randomicity of network suffered from security attacks and the uncertainty of network security situation, it is difficult to precisely predict network security situation in single predication model. Therefore, an immune-based combination predication model for network security situation (ICPM) is proposed by using GM(1,1) and artificial immune predication model (AIPM). In ICPM, the trend component of a time series of network security situation are predicted by GM(1,1) model, and the random component of that are predicated by AIPM model, and then the slide window mechanism is introduced to be used for dynamically predicting network security situation. Experimental results show that ICPM model can forecast the future network security situation real-timely and correctly, and simultaneity its results are more precise than that of GM(1,1) model and AIPM model.