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A Data Obfuscation Based on State Transition Graph of Mealy Automata

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Intelligent Computing Theory (ICIC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8588))

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Abstract

Mealy automata model can be used to obfuscate constants and strings in programs, as to the obfuscation, the structure of state transition graph of mealy machine is simple and easy to test. To solve this problem, a data obfuscation based on state transition graph of mealy machine is proposed. With iteration of state transition graph of mealy machine, redundant states, transition functions and output functions based on probability are added into the graph, and then constants and strings in programs are obfuscated by the mealy machine. Analysis and experiment validated that redundant states and transition functions can increase the complexity of the structure of state transition graph. Output functions based on probability can increase the randomization of output obfuscated data. Obfuscation can be effective to improve the performance of mealy machine to resist static and dynamic reverse analysis.

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References

  1. Collberg, C., Thomborson, C.: Watermarking, Tamper-Proofing, and Obfuscation-Tools for Software Protection. IEEE Transactions on Software Engineering 28(8), 735–746 (2002)

    Article  Google Scholar 

  2. Collberg, C., Thomborson, C., Low, D.: A taxonomy of obfuscating transformations. Technical Report 148, Department of Computer Science, the University of Auckland, New Zealand (1997)

    Google Scholar 

  3. Chan, J., Yang, W.: Advanced obfuscation techniques for Java bytecode. Journal of Systems and Software 71(1/2), 1–10 (2004)

    Article  Google Scholar 

  4. Xu, W., Zhang, F., Zhu, S.: The power of obfuscation techniques in malicious JavaScript code: A measurement study. In: Proceedings of 7th IEEE International Conference on Malicious and Unwanted Software, pp. 9–16 (2012)

    Google Scholar 

  5. Sosonkin, M., Naumovich, G., Memon, N.: Obfuscation of design intent in object-oriented applications. In: Proceedings of 3rd ACM Workshop on Digital Rights Management, pp. 142–153 (2003)

    Google Scholar 

  6. Popov, I.V., Debray, S.K., Andrews, G.R.: Binary obfuscation using signals. In: Proceedings of 16th USENIX Security Symposium, pp. 275–290 (2007)

    Google Scholar 

  7. Balachandran, V., Emmanuel, S.: Potent and Stealthy Control Flow Obfuscation by Stack Based Self-Modifying Code. IEEE Transactions on Information Forensics and Security 8(4), 669–681 (2013)

    Article  Google Scholar 

  8. Badger, L., D’Anna, L., Kilpatrick, D., et al.: Self-protecting mobile agents obfuscation techniques evaluation report. Technical Report 01-036, NAI Labs (2001)

    Google Scholar 

  9. Collberg, C., Thomborson, C., Low, D.: Breaking abstractions and unstructuring data structures. In: Proceedings of IEEE International Conference on Computer Languages, pp. 28–38 (1998)

    Google Scholar 

  10. Praveen, S., Sojan, P.: Array Data Transformation for Source Code Obfuscation. Proceedings of World Academy of Science, Engineering and Technology 1, 83–87 (2007)

    Google Scholar 

  11. Zhu, W., Thomborson, C.D., Wang, F.Y.: Obfuscate arrays by homomorphic functions. In: Proceedings of IEEE International Conference on Granular Computing, pp. 770–773 (2006)

    Google Scholar 

  12. Xin, Z., Chen, H., Han, H., Mao, B., Xie, L.: Misleading malware similarities analysis by automatic data structure obfuscation. In: Burmester, M., Tsudik, G., Magliveras, S., Ilić, I. (eds.) ISC 2010. LNCS, vol. 6531, pp. 181–195. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  13. Collberg, C., Nagra, J.: Surreptitious software: obfuscation, watermarking, and tamper-proofing for software protection, pp. 269–271. Addison-Wesley (2009)

    Google Scholar 

  14. George, H.M.: A method for synthesizing sequential circuits. Bell System Technical Journal 34(5), 1045–1079 (1955)

    Article  MathSciNet  Google Scholar 

  15. McCabe, T.: A complexity measure. IEEE Transaction on Software Engineering SE-2(4), 308–320 (1976)

    Article  MathSciNet  Google Scholar 

  16. Schrittwieser, S., Katzenbeisser, S.: Code Obfuscation against Static and Dynamic Reverse Engineering. In: Filler, T., Pevný, T., Craver, S., Ker, A. (eds.) IH 2011. LNCS, vol. 6958, pp. 270–284. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  17. Cesare, S., Xiang, Y.: Software Similarity and Classification, pp. 63–70 (2012)

    Google Scholar 

  18. Patrick, P.F., Lucas, C.K., Yiu, S.M.: Heap Graph Based Software Theft Detection. IEEE Transactions on Information Forensics and Security 8(1), 101–110 (2013)

    Article  Google Scholar 

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Xie, X., Liu, F., Lu, B. (2014). A Data Obfuscation Based on State Transition Graph of Mealy Automata. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_58

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  • DOI: https://doi.org/10.1007/978-3-319-09333-8_58

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09332-1

  • Online ISBN: 978-3-319-09333-8

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