Detection technology for unknown virus based on data farming

Hao Bin Shi, Wen Bin Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

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.

Original languageEnglish
Title of host publication2010 2nd IITA International Conference on Geoscience and Remote Sensing, IITA-GRS 2010
Pages96-99
Number of pages4
DOIs
StatePublished - 2010
Event2010 2nd IITA Conference on Geoscience and Remote Sensing, IITA-GRS 2010 - Qingdao, China
Duration: 28 Aug 201031 Aug 2010

Publication series

Name2010 2nd IITA International Conference on Geoscience and Remote Sensing, IITA-GRS 2010
Volume1

Conference

Conference2010 2nd IITA Conference on Geoscience and Remote Sensing, IITA-GRS 2010
Country/TerritoryChina
CityQingdao
Period28/08/1031/08/10

Keywords

  • Data farming
  • Naive bayes
  • Unknown virus
  • Virus detection

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