DocumentCode
529614
Title
Detection technology for unknown virus based on data farming
Author
Shi Hao-bin ; Li Wen-Bin
Author_Institution
Dept. of Comput. Sci. & Eng., Northwestern Polytech. Univ., Xi´an, China
Volume
1
fYear
2010
fDate
28-31 Aug. 2010
Firstpage
96
Lastpage
99
Abstract
In order to improve the detection rate of unknown virus, this paper presented a detection technology for unknown computer virus based on data farming, which synthetically considered the types of viruses, feature extraction methods for viruses of different types, data classification algorithms and other factors. Firstly, this technology extracted the behavior feature of the files to be executed, and then analyzed the extracted feature data by means of improved data farming technology which absorbed naive bayes classification algorithm to detect whether the file to be executed contained viruses. Experimental results showed that this technology had the higher accuracy and lower error rate in unknown computer viruses detection.
Keywords
Bayes methods; computer viruses; feature extraction; pattern classification; behavior feature; data classification algorithms; data farming; error rate; feature extraction methods; naive bayes classification algorithm; unknown computer viruses detection; Accuracy; Buildings; Classification algorithms; Computational modeling; data farming; naive bayes; unknown virus; virus detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing (IITA-GRS), 2010 Second IITA International Conference on
Conference_Location
Qingdao
Print_ISBN
978-1-4244-8514-7
Type
conf
DOI
10.1109/IITA-GRS.2010.5602957
Filename
5602957
Link To Document