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Most existing spreading models for network viruses are developed refereing to the epidemic models for biological viruses. However, Why most network viruses spread much slower than those models predicate? Why most network viruses still exist when they go beyond the threshold predicated by those models? Contrary to the prior models, the paper points out network viruses have different spreading features compared with biological viruses, such as the connectivity rate and cure rate are both functions of the time which are also key factors to affect the spreading of viruses. Based on which the paper constructs a more general epidemiological model for the network viruses. For several particular cases the paper presents the simulations of the connectivity rate and cure rate and find they are consistent well with the statistics of some real viruses. Thus the paper opens one path to modifying the traditional epidemic models.