Abstract: A network security posture prediction mechanism based on differential WGAN(Wasserstein- GAN) is presented in this paper.This mechanism uses Generative adversarial network (GAN) to simulate the development process of the situation,and realizes the situation forecast from the time Dimension.In order to solve the problem of difficult network training,collapse mode and gradient instability of GAN,this paper put forward the method by using Wasserstein distance as the loss function of GAN and adding the difference term in the loss function,to improve the classification precision of the situation value.The stability of the differential WGAN network was also proved.Experimental andanalysis results show that this mechanism has advantages over other mechanisms in terms of convergence,accuracy and complexity.

Key words: Difference, Generative adversarial network, Situation forecast, Situational awareness, Wasserstein-GAN