Information security forecast based on artificial neural networks and grey set pare analysis

Utilizing the artificial neural networks and grey set pare analysis(GSPA), this paper presents a model forecasting the infection rate of computer viruses based on the percentage of four major consequences of virus infection: browser hijack, account theft, illegal remote control as well as system or network failure. The correlation between the infection rate of computer viruses and four other factors is analyzed and sorted by GSPA.