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Journal in Computer Virology

, Volume 2, Issue 3, pp 163–186 | Cite as

Non-signature based virus detection

Towards establishing a unknown virus detection technique using SOM
  • In Seon YooEmail author
  • Ulrich Ultes-Nitsche
Original Paper

Abstract

A non-signature-based virus detection approach using Self-Organizing Maps (SOMs) is presented in this paper. Unlike classical virus detection techniques using virus signatures, this SOM-based approach can detect virus-infected files without any prior knowledge of virus signatures. Exploiting the fact that virus code is inserted into a complete file which was built using a certain compiler, an untrained SOM can be trained in one go with a single virus-infected file and will then present an area of high density data, identifying the virus code through SOM projection. The virus detection approach presented in this paper has been tested on 790 different virus-infected files, including polymorphic and encrypted viruses. It detects viruses without any prior knowledge – e.g. without knowledge of virus signatures or similar features – and is therefore assumed to be highly applicable to the detection of new, unknown viruses. This non-signature-based virus detection approach was capable of detecting 84% of the virus-infected files in the sample set which included, as already mentioned, polymorphic and encrypted viruses. The false positive rate was 30%. The combination of the classical virus detection technique for known viruses and this SOM-based technique for unknown viruses can help systems be even more secure.

Keywords

Malicious Code Parasitic Virus Virus Signature Unknown Virus Codebook Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag France 2006

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of FribourgFribourgSwitzerland

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