Information Security Forecast Based on Artificial Neural Networks and Grey Set Pare Analysis

摘要：

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.

关键词： artificial neural networks grey set pare analysis infection rate forecast

作者: Dingtian Zhang Xiaoxi Zhang

作者单位: Department of Computer Science & Technology Tsinghua University Beijing, china Normal College Beijing Union University Beijing China

会议类型: 国际会议

会议名称: 2011 9th International Conference on Reliability,Maintainability and Safety(第九届国际可靠性、维修性、安全性会议 ICRMS2011)

会议地点: 贵阳

会议语种:英文

页码: 473-476

在线出版日期: 2011-06-12（万方平台首次上网日期，不代表论文的发表时间）