DocumentCode
2684201
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
fYear
2011
fDate
12-15 June 2011
Firstpage
473
Lastpage
476
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Reliability, Maintainability and Safety (ICRMS), 2011 9th International Conference on
Conference_Location
Guiyang
Print_ISBN
978-1-61284-667-5
Type
conf
DOI
10.1109/ICRMS.2011.5979346
Filename
5979346
Link To Document