Malware biodiversity using static analysis

Jeremy D. Seideman, Bilal Khan, Antonio Cesar Vargas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Malware is constantly changing and is released very rapidly, necessarily to remain effective in the changing computer landscape. Some malware files can be related to each other; studies that indicate that malware samples are similar often base that determination on common behavior or code. Given, then, that new malware is often developed based on existing malware, we can see that some code fragments, behavior, and techniques may be influencing more development than others. We propose a method by which we can determine the extent that previously released malware is influencing the development of new malware. Our method allows us to examine the way that malware changes over time, allowing us to look at trends in the changing malware landscape. This method, which involves a historical study of malware, can then be extended to investigate specific behaviors or code fragments. Our method shows that, with respect to the method in which we compared malware samples, over 64% of malware samples that we analyzed are contributing to the biodiversity of the malware ecosystem and influencing new malware development.

Original languageEnglish (US)
Title of host publicationFuture Network Systems and Security - 1st International Conference, FNSS 2015, Proceedings
EditorsSelwyn Piramuthu, Wei Zhou, Robin Doss
PublisherSpringer Verlag
Pages139-155
Number of pages17
ISBN (Electronic)9783319192093
DOIs
StatePublished - 2015
Event1st International Conference on Future Network Systems and Security, FNSS 2015 - Paris, France
Duration: Jun 11 2015Jun 13 2015

Publication series

NameCommunications in Computer and Information Science
Volume523
ISSN (Print)1865-0929

Other

Other1st International Conference on Future Network Systems and Security, FNSS 2015
CountryFrance
CityParis
Period6/11/156/13/15

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

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  • Cite this

    Seideman, J. D., Khan, B., & Vargas, A. C. (2015). Malware biodiversity using static analysis. In S. Piramuthu, W. Zhou, & R. Doss (Eds.), Future Network Systems and Security - 1st International Conference, FNSS 2015, Proceedings (pp. 139-155). (Communications in Computer and Information Science; Vol. 523). Springer Verlag. https://doi.org/10.1007/978-3-319-19210-9_10