skip to main content
10.1145/1569901.1570111acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
research-article

Evolvable malware

Authors Info & Claims
Published:08 July 2009Publication History

ABSTRACT

The concept of artificial evolution has been applied to numerous real world applications in different domains. In this paper, we use this concept in the domain of virology to evolve computer viruses. We call this domain as "Evolvable Malware". To this end, we propose an evolutionary framework that consists of three modules: (1) a code analyzer that generates a high-level genotype representation of a virus from its machine code, (2) a genetic algorithm that uses the standard selection, cross-over and mutation operators to evolve viruses, and (3) the code generator converts the genotype of a newly evolved virus to its machinelevel code. In this paper, we validate the notion of evolution in viruses on a well-known virus family, called Bagle. The results of our proof-of-concept study show that we have successfully evolved new viruses-previously unknown and known-variants of Bagle-starting from a random population of individuals. To the best of our knowledge, this is the first empirical work on evolution of computer viruses. In future, we want to improve this proof-of-concept framework into a full-blown virus evolution engine.

References

  1. F-Secure Virus Description Database, available at http://www.f-secure.com/v-descs/.Google ScholarGoogle Scholar
  2. The IDA pro disassembler and debugger, available at http://www.hex-rays.com/idapro/.Google ScholarGoogle Scholar
  3. Offensive Computing, available at http://www.offensivecomputing.net.Google ScholarGoogle Scholar
  4. VX Heavens Virus Collection, VX Heavens website, available at http://hvx.netlux.org.Google ScholarGoogle Scholar
  5. Kaspersky Lab, VirusList.Com, available at http://www.viruslist.com/en/viruses/encyclopedia/.Google ScholarGoogle Scholar
  6. J.M. Bauer, J.G. Michel and Y. Wu. "ITU Study on the Financial Aspects of Network Security: Malware and Spam", ICT Applications and Cybersecurity Division, International Telecommunication Union, Final Report, July 2008, available at http://www.itu.int/ITU-D/cyb/cybersecurity/docs/itu-study-financial-aspects-of-malware-and-spam.pdf.Google ScholarGoogle Scholar
  7. F. Cohen, "Computer Viruses", PhD thesis, University of Southern California, 1985.Google ScholarGoogle Scholar
  8. G. Gabrani, P. Bhargava, B. Bhawana and G.S. Gill. "Use of Genetic Algorithms for Indian Music Mixing", ACM Ubiquity, 9(10), Article 1, ACM Press, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. J.R. Koza, F.H. Bennett, D. Andre and M.A. Keane "Reuse, parameterized reuse, and hierarchical reuse of substructures in evolving electrical circuits using genetic programming", International Conference on Evolvable Systems: From Biology to Hardware, Volume 1259 of Lecture Notes in Computer Science, pp. 312--326, Springer, UK, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. J.R. Koza and J.P. Rice, "Automatic Programming of Robots using Genetic Programming" 10th National Conference on Artificial Intelligence, pp. 194--201, Association for the Advancement of Artificial Intelligence (AAAI), 1992.Google ScholarGoogle Scholar
  11. M.A. Ludwing, "Computer Viruses, Artificial Life and Evolution", American Eagle Publications, 1993.Google ScholarGoogle Scholar
  12. J. Gray, R. Klefstad, "Adaptive and Evolvable Software Systems: Techniques, Tools, and Applications", 38th Annual Hawaii International Conference on System Sciences (HICSS), page 274, IEEE Press, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. M.H. Marghny and A.F. Ali, "Web Mining based on Genetic Algorithm", IGCST International Journal on Artificial Intelligence and Machine Learning, Special Issue on AI Classification&Analysis Techniques, 2006.Google ScholarGoogle Scholar
  14. H.J.F. Moen and S. Kristoffersen, "Multi-resistant radar jamming using genetic algorithms", Genetic and Evolutionary Computation Conference (GECCO), pp. 1595--1602, ACM Press, USA, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. D. Montana, T. Hussain and T. Saxena, "Adaptive Reconfiguration Of Data Networks Using Genetic Algorithms", Genetic and Evolutionary Computation Conference (GECCO), pp. 1141--1149, ACM Press, USA, 2002.Google ScholarGoogle Scholar
  16. K. Rozinov, "Reverse code engineering: An In-depth Analysis of the Bagle Virus", 6th Annual IEEE SMC Information Assurance Workshop (IAW), pp. 380--387, IEEE Press, USA, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  17. E.H. Spafford, "Computer viruses as Artificial Life", Journal of Artificial Life, 1(3), pp. 249--265, MIT Press, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. G. Stein, B. Chen, A.S. Wu and K.A. Hua, "Decision tree classifier for Network Intrusion Detection with GA-based Feature Selection", 43rd Annual ACM Southeast Regional Conference, pp. 136--141, USA, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. O.D. Tabibi, M. Koppel and N.S. Netanyahu, "Genetic algorithms for mentor-assisted evaluation function optimization", Genetic and Evolutionary Computation Conference (GECCO), pp. 1469--1476, ACM Press, USA, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. G. Weinberg, M. Godfrey, A. Rae and J. Rhoads, "A Real-time Genetic Algorithm in Human-robot Musical Improvisation", 4th International Symposium on Computer Music Modeling and Retrieval, Sense of Sounds, Volume 4969 of Lecture Notes in Computer Science, pp. 351--359, Springer, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. D. Whitley, "An Overview of Evolutionary Algorithms: Practical Issues and Common Pitfalls", Information and Software Technology, 43(14), pp. 817--831, 2001.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Evolvable malware

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
        July 2009
        2036 pages
        ISBN:9781605583259
        DOI:10.1145/1569901

        Copyright © 2009 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 8 July 2009

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        Overall Acceptance Rate1,669of4,410submissions,38%

        Upcoming Conference

        GECCO '24
        Genetic and Evolutionary Computation Conference
        July 14 - 18, 2024
        Melbourne , VIC , Australia

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader