ECFGM: enriched control flow graph miner for unknown vicious infected code detection

1. Aggarwal C., Wang H.: Managing and Mining Graph Data vol 40. Springer, New York (2010)

   Book  Google Scholar 

2. Anju, S., Harmya, P., Jagadeesh, N., Darsana, R.: Malware detection using assembly code and control flow graph optimization. In: Proceedings of the 1st Amrita ACM-W Celebration on Women in Computing in India, p. 65. ACM (2010)

3. Bayer U., Moser A., Kruegel C., Kirda E.: Dynamic analysis of malicious code. J. Comput. Virol. 2(1), 67–77 (2006)

   Article  Google Scholar 

4. Bilar D.: On callgraphs and generative mechanisms. J. Comput. Virol. 3(4), 285–297 (2007)

   Article  MathSciNet  Google Scholar 

5. Bruschi, D., Martignoni, L., Monga, M.: Detecting self-mutating malware using control-flow graph matching. Detection of Intrusions and Malware & Vulnerability Assessment pp. 129–143 (2006)

6. Harley D.: Making sense of anti-malware comparative testing. Inf. Secur. Tech. Rep. 14(1), 7–15 (2009)

   Article  Google Scholar 

7. Hofmeyr S., Forrest S., Somayaji A.: Intrusion detection using sequences of system calls. J. Comput. Secur. 6(3), 151–180 (1998)

   Google Scholar 

8. Idika N., Mathur A.: A survey of malware detection techniques, pp. 48. Purdue University, USA (2007)

   Google Scholar 

9. Kostakis, O., Kinable, J., Mahmoudi, H., Mustonen, K.: Improved call graph comparison using simulated annealing. In: Proceedings of the 2011 ACM Symposium on Applied Computing, pp. 1516–1523. ACM (2011)

10. Lai, Y.: A feature selection for malicious detection. In: Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2008. SNPD’08. Ninth ACIS International Conference on, pp. 365–370. IEEE (2008)

11. Menahem E., Shabtai A., Rokach L., Elovici Y.: Improving malware detection by applying multi-inducer ensemble. Comput. Stat. Data Anal. 53(4), 1483–1494 (2009)

    Article  MathSciNet  MATH  Google Scholar 

12. Moser, A., Kruegel, C., Kirda, E.: Limits of static analysis for malware detection. In: Computer Security Applications Conference, 2007. ACSAC 2007. Twenty-Third Annual, pp. 421–430. IEEE (2007)

13. PE-Explorer:(2011) http://www.pe-explorer.com/peexplorer-tour-disassembler.htm

14. Perdisci R., Lanzi A., Lee W.: Classification of packed executables for accurate computer virus detection. Pattern Recognit. Lett. 29(14), 1941–1946 (2008)

    Article  Google Scholar 

15. Picard, R., Cook, R.: Cross-validation of regression models. Journal of the American Statistical Association pp. 575–583(1984)

16. Shankarapani M., Ramamoorthy S., Movva R., Mukkamala S.: Malware detection using assembly and api call sequences. J. Comput. Virol. 7(2), 107–119 (2011)

    Article  Google Scholar 

17. Sulaiman, A., Ramamoorthy, K., Mukkamala, S., Sung, A.: Malware examiner using disassembled code (medic). In: Information Assurance Workshop, 2005. IAW’05. Proceedings from the Sixth Annual IEEE SMC, pp. 428–429. IEEE (2005)

18. Szor P.: The Art of Computer Virus Research and Defense. Addison-Wesley Professional, (2005)

19. Tesauro G., Kephart J., Sorkin G.: Neural networks for computer virus recognition. IEEE expert 11(4), 5–6 (1996)

    Article  Google Scholar 

20. Tong, W., Jin, R.: Semi-supervised learning by mixed label propagation. In: Proceedings of the National Conference on Artificial Intelligence, vol. 22, p. 651. AAAI Press, Menlo Park, MIT Press, London 1999 (2007)

21. Vinod, P., Laxmi, V., Gaur, M., Kumar, G., Chundawat, Y.: Static CFG Analyzer for Metamorphic Malware Code. In: Proceedings of the 2nd International Conference on Security of Information and Networks, pp. 225–228. ACM (2009)

22. Wang, J., Deng, P., Fan, Y., Jaw, L., Liu, Y.: Virus detection using data mining techinques. In: Security Technology, 2003. In: Proceedings. IEEE 37th Annual 2003 International Carnahan Conference. pp. 71–76. IEEE (2003)

23. Wespi, A., Dacier, M., Debar, H.: Intrusion detection using variable-length audit trail patterns. In: Recent advances in intrusion detection, pp. 110–129. Springer (2000)

24. You, I., Yim, K.: Malware obfuscation techniques: A brief survey. In: Broadband, Wireless Computing, Communication and Applications (BWCCA), 2010 International Conference on, pp. 297–300. IEEE (2010)

25. Zaidan A., Zaidan B., Othman F.: New technique of hidden data in pe-file with in unused area one. Int. J. Comput. Electr. Eng. (IJCEE) 1(5), 669–678 (2009)

    Google Scholar 

26. Zhang, B., Yin, J., Hao, J., Wang, S., Zhang, D.: New malicious code detection based on n-gram analysis and rough set theory. Computational Intelligence and Security pp. 626–633 (2007)

27. Zolkipli, M., Jantan, A.: A framework for malware detection using combination technique and signature generation. In: Computer Research and Development, 2010 Second International Conference on, pp. 196–199. IEEE (2010)

28. Zuo Z., Zhou M.: Some further theoretical results about computer viruses. Comput. J. 47(6), 627–633 (2004)

    Article  Google Scholar 

29. Zuo Z., Zhu Q., Zhou M.: On the time complexity of computer viruses. IEEE Trans. Inf. Theory 51(8), 2962–2966 (2005)

    Article  MathSciNet  Google Scholar 

Download references