Title :
Information security forecast based on artificial neural networks and grey set pare analysis
Author :
Zhang, Dingtian ; Zhang, Xiaoxi
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Abstract :
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.
Keywords :
computer viruses; forecasting theory; grey systems; neural nets; security of data; telecontrol; GSPA; account theft; artificial neural networks; browser hijack; computer viruses; grey set pare analysis; illegal remote control; infection rate forecasting; information security forecasting; network failure; system failure; Artificial neural networks; Computer viruses; Correlation; Information security; artificial neural networks; grey set pare analysis; infection rate forecast;
Conference_Titel :
Reliability, Maintainability and Safety (ICRMS), 2011 9th International Conference on
Conference_Location :
Guiyang
Print_ISBN :
978-1-61284-667-5
DOI :
10.1109/ICRMS.2011.5979346
