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Evolvable Malware

Evolvable Malware. Sadia Noreen, Sahafq Murtaza , M . Zubair Shafiq , Muddassar Farooq National University of Computer and Emerging Sciences (FAST-NUCES) Next Generation Intelligent Networks Research Center ( nexGIN RC) Islamabad, 44000, Pakistan. Citations.

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Evolvable Malware

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  1. Evolvable Malware SadiaNoreen, SahafqMurtaza, M. ZubairShafiq, MuddassarFarooq National University of Computer and Emerging Sciences (FAST-NUCES) Next Generation Intelligent Networks Research Center (nexGIN RC) Islamabad, 44000, Pakistan

  2. Citations Sadia Noreen, Shafaq Murtaza, M. Zubair Shafiq, Muddassar Farooq. 1. Evolvable Malware. In Proceedings of the Genetic and Evolutionary Computation Conference(GECCO), ACM Press, 2009. 2. Using Formal Grammar and Genetic Operators to Evolve Malware. In Recent Advances in Intrusion Detection (RAID), Springer LNCS, 2009.

  3. Relevance of Computer Malware to ALife • ALife: Studies the logic of living systems in artificial environment • Evolution: Property of ALife • Malware, if considered to be alive, must possess the fundamental property of ALife – evolution.

  4. Objectives • To provide an abstract representation that maps all the features of malware— Bagle • To evolve the malware – evolution in its true sense. • To test the evolved malware using anti-virus software.

  5. Finally Virus Created!!! RATHER HUMAN WHOMPING!!!

  6. Evolvable Malware Framework

  7. Abstract Representation

  8. Experimental Setup (2) GA Parameters: Population Size=500 Crossover Rate=0.75 Mutation Rate=0.005 # of Generations=500

  9. Experimental Results

  10. Criteria Satisfied GECCO 2009 – Anonymous Reviewer Comments • “The paper is very interesting and well written overall and definitely worth to • be published.” • “I found the paper quite interesting. Further research is most welcomed.” D: The result is publishable in its own right as a new scientific result independent of the fact that the result was mechanically created.

  11. Criteria Satisfied Polymorphic Engine Metamorphic Engines Our Engine Virus Code Virus Code Virus Code Genetic Operators Encryption Routine Virus Code . . . NOP Decryption Routine Virus Code E: The result is equal to or better than the most recent human-created solution to a long-standing problem for which there has been a succession of increasingly better human-created solutions.

  12. Criteria Satisfied Result is better than the result that was considered as an achievement so far… • Polymorphic and metamorphic engines produce viruses that belong to the same • class i.e. the evolved viruses are the variants of the same class e.g. Bagle.a, • Bagle.b etc. • The viruses produced by our engine do not belong to just one class i.e. the • evolved viruses may belong to the different classes of malware e.g. Bagle class, • W32.Sality etc. F: Theresult is equal to or better than a result that was considered an achievement in its field at the time it was first discovered.

  13. Criteria Satisfied Reverse Engineering of a class of malware • Analyzing the disassembled code of a class of malware and extracting the • features of our interest was a challenging task. • There has always been a talk about malware evolution by applying genetic • operators but there was no comprehensive achievement since the difficulty • level of the problem domain was very high. G: The result solves a problem of indisputable difficulty in its field.

  14. Human Competitive? • Evolve malware without human intervention • Produces new variants of malware within NO TIME as compared to virus writer

  15. Impact • The result is of great importance in security research • Antivirus product – Testing against zero day attacks • Evolving software

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