Information Security Forecast Based on Artificial Neural Networks and Grey Analyze

Based on the artificial neural networks and grey correlation analyze, this paper presents a model forecasting the infection rate of computer viruses according to the number of vulnerabilities, the percentage of viruses infecting via web browsing and downloading and the percentage of viruses infecting via portable storage media. The prediction is realized precisely by MATLAB. The three factors are analyzed and sorted by grey correlation analyze, which reveals that the percentage of viruses infecting via on-line browsing has the most significant influence on the infection rate of computer viruses.