Development of unified mathematical model of programming modules obfuscation process based on graphic evaluation and review method

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.206232

Keywords:

GERT model, programming modules obfuscation, program code, gamma distribution, java

Abstract

A set of algorithms of programming modules obfuscation is synthesized, which differs from the known ones by taking into account the variability of data types. This made it possible to describe these processes at the upper strategic level of formalization. The possibilities of using GERT models to apply various options of the distribution laws and their parameters in the transition from state to state are investigated. A unified GERT model of the programming modules obfuscation process is developed. This model differs from the known ones by the paradigm of using the mathematical apparatus of gamma distribution as the key one at all stages of modeling the obfuscation process. This made it possible to achieve model unification in the conditions of GERT network modification. The expectation and variance of the runtime of a random value of the obfuscation and deobfuscation time of programming modules are calculated. The results of the study showed that for the developed mathematical model, the addition of another obfuscation process leads to an increase in the runtime variance by 12 %, and when removed from the system, it decreases by 13 %. The runtime expectation changes exponentially. So, when removing the node, the expectation decreases by 9 %, and when increasing by 1 node, the expectation increases by 26 %. This shows the insignificance of changes in the studied characteristics under the conditions of model modification and confirms the hypothesis of model unification in conditions of using the mathematical apparatus of gamma distribution as the main one. These results allow the developer to predict the behavior of the programming modules protection system in terms of runtime. This allows reducing the time to decide on the feasibility of the obfuscation process

Author Biographies

Serhii Semenov, National Technical University “Kharkiv Polytechnic Institute” Kyrpychova str., 2, Kharkiv, Ukraine, 61002

Doctor of Technical Sciences, Professor

Department of Computer Engineering and Programming

Viacheslav Davydov, National Technical University “Kharkiv Polytechnic Institute” Kyrpychova str., 2, Kharkiv, Ukraine, 61002

PhD

Department of Computer Engineering and Programming

Oksana Lipchanska, National Technical University “Kharkiv Polytechnic Institute” Kyrpychova str., 2, Kharkiv, Ukraine, 61002

PhD

Department of Computer Engineering and Programming

Maksym Lipchanskyi, National Technical University “Kharkiv Polytechnic Institute” Kyrpychova str., 2, Kharkiv, Ukraine, 61002

PhD, Associate Professor

Department of Computer Engineering and Programming

References

  1. On Protection of Information in Automated Systems (1994). Verkhovna Rada of Ukraine. Available at: https://zakon.rada.gov.ua/laws/show/80/94-%D0%B2%D1%80#top
  2. On Copyright and Related Rights (1994). Verkhovna Rada of Ukraine. Available at: https://zakon.rada.gov.ua/laws/show/3792-12#Text
  3. Galatenko, V. A. (2016). Osnovy informatsionnoy bezopasnosti. Moscow: Natsional'niy Otkrytiy Universitet "INTUIT", 267.
  4. Raskin, L. G., Pustovoytov, P. E., Abdel'hamid Saed Ahmad, S. A. (2006). Markovskaya approksimatsiya nemarkovskih sistem. Informatsiyno-keruiuchi systemy na zaliznychnomu transporti, 1, 57–60. Available at: http://repository.kpi.kharkov.ua/bitstream/KhPI-Press/6801/1/2006_Raskin_Markovskaya.pdf
  5. Denning, P. J., Lewis, T. G. (2016). Exponential laws of computing growth. Communications of the ACM, 60 (1), 54–65. doi: https://doi.org/10.1145/2976758
  6. Strzałka, D., Dymora, P., Mazurek, M. (2018). Modified stretched exponential model of computer system resources management limitations – The case of cache memory. Physica A: Statistical Mechanics and Its Applications, 491, 490–497. doi: https://doi.org/10.1016/j.physa.2017.09.012
  7. Kovalenko, O. V., Hochkin, N. I. (2015). Solution of the system of renewal Markov equations using the approximation of asymptotic series. Trudy MFTI, 7 (2), 5–19. Available at: https://mipt.ru/upload/medialibrary/26d/5-19.pdf
  8. Lacasa, L., Mariño, I. P., Miguez, J., Nicosia, V., Roldán, É., Lisica, A. et. al. (2018). Multiplex Decomposition of Non-Markovian Dynamics and the Hidden Layer Reconstruction Problem. Physical Review X, 8 (3). doi: https://doi.org/10.1103/physrevx.8.031038
  9. Distefano, S., Longo, F., Scarpa, M. (2017). Marking dependency in non-Markovian stochastic Petri nets. Performance Evaluation, 110, 22–47. doi: https://doi.org/10.1016/j.peva.2017.03.001
  10. Jiang, S., Yang, S. (2016). An Improved Multiobjective Optimization Evolutionary Algorithm Based on Decomposition for Complex Pareto Fronts. IEEE Transactions on Cybernetics, 46 (2), 421–437. doi: https://doi.org/10.1109/tcyb.2015.2403131
  11. Semenov, S., Sira, O., Kuchuk, N. (2018). Development of graphic­analytical models for the software security testing algorithm. Eastern-European Journal of Enterprise Technologies, 2 (4 (92)), 39–46. doi: https://doi.org/10.15587/1729-4061.2018.127210
  12. Sheng, Z., Hu, Q., Liu, J., Yu, D. (2017). Residual life prediction for complex systems with multi-phase degradation by ARMA-filtered hidden Markov model. Quality Technology & Quantitative Management, 16 (1), 19–35. doi: https://doi.org/10.1080/16843703.2017.1335496
  13. Hu, L., Liu, Z., Hu, W., Wang, Y., Tan, J., Wu, F. (2020). Petri-net-based dynamic scheduling of flexible manufacturing system via deep reinforcement learning with graph convolutional network. Journal of Manufacturing Systems, 55, 1–14. doi: https://doi.org/10.1016/j.jmsy.2020.02.004
  14. Semyonov, S. G., Gavrilenko, S. Y., Chelak, V. V. (2017). Information processing on the computer system state using probabilistic automata. 2017 2nd International Ural Conference on Measurements (UralCon). doi: https://doi.org/10.1109/uralcon.2017.8120680
  15. Burgelman, J., Vanhoucke, M. (2019). Computing project makespan distributions: Markovian PERT networks revisited. Computers & Operations Research, 103, 123–133. doi: https://doi.org/10.1016/j.cor.2018.10.017
  16. Kovalenko, O. (2017). DOM XSS vulnerability testing technology. Ukrainian Scientific Journal of Information Security, 23 (2), 73–79. doi: https://doi.org/10.18372/2225-5036.23.11821
  17. Shibanov, A. P. (2003). Finding the Distribution Density of the Time Taken to Fulfill the GERT Network on the Basis of Equivalent Simplifying Transformations. Automation and Remote Control, 64, 279–287. doi: https://doi.org/10.1023/A:1022267115444
  18. Venkatesh, S., Ertaul, L. (2005). Novel Obfuscation Algorithms for Software Security. Proceedings of the 2005 International Conference on Software Engineering Research and Practice, 1, 209–215.
  19. Mohsen, R., Miranda Pinto, A. (2015). Algorithmic Information Theory for Obfuscation Security. Proceedings of the 12th International Conference on Security and Cryptography. doi: https://doi.org/10.5220/0005548200760087

Downloads

Published

2020-06-30

How to Cite

Semenov, S., Davydov, V., Lipchanska, O., & Lipchanskyi, M. (2020). Development of unified mathematical model of programming modules obfuscation process based on graphic evaluation and review method. Eastern-European Journal of Enterprise Technologies, 3(2 (105), 6–16. https://doi.org/10.15587/1729-4061.2020.206232