Genetic Decompilation Concept of the Telecommunication Devices Machine Code
https://doi.org/10.31854/1813-324X-2021-7-4-95-109
Abstract
Reverse engineering correct source code from a machine code to find and neutralize vulnerabilities is the most pressing problem for the field of telecommunications equipment. The decompilation techniques applicable for this have potentially reached their evolutionary limit. As a result, new concepts are required that can make a quantum leap in problem solving. Proceeding from this, the paper proposes the concept of genetic decompilation, which is a solution to the problem of multiparameter optimization in the form of iterative approximation of instances of the source code to the "original" one which will compile to the given machine code. This concept is tested by conducting a series of experiments with the developed software prototype using a basic example of machine code. The results of the experiments prove the proof of the concept, thereby suggesting new innovative directions for ensuring information security in this subject area.
Keywords
About the Author
K. IzrailovRussian Federation
St. Petersburg, 193232, Russian Federation
St. Petersburg, 199178, Russian Federation
References
1. Gurin R.E. Review and Analysis of Tools that Verify the Binary Code of the Program. Novye informatsionnye tekhnologii v avtomatizirovannykh sistemakh. 2014;17:514‒518. (in Russ.)
2. Tikhonov A.Yu., Avetisyan A.I. Combined (Static and Dynamic) Analysis of Binary Code. Proceedings of the Institute for System Programming of the RAS. 2012;22:131‒152. (in Russ.)
3. Kaushan V.V. Buffer Overrun Detection Method in Binary Code. Proceedings of the Institute for System Programming of the RAS. 2016;28(5):135‒144. (in Russ.)
4. Bugerya A.B., Efimov V.Yu., Kulagin I.I., Padaryan V.A., Solovev M.A., Tikhonov A.Yu. A Software Complex for Revealing Malicious Behavior in Untrusted Binary Code. Proceedings of the Institute for System Programming of the RAS. 2019;31(6):33‒64. (in Russ.) DOI:10.15514/ISPRAS-2019-31(6)-3
5. Buinevich M., Izrailov K., Vladyko A. Metric of vulnerability at the base of the life cycle of software representations. Proceedings of the 20th International Conference on Advanced Communication Technology, ICACT, 11‒14 February 2018, Chuncheon, South Korea. IEEE; 2018. p.1‒8. DOI:10.23919/ICACT.2018.8323940
6. Troshina K.N., Chernov A.V. Type Reconstruction for C Decompilation. Journal of Applied Informatics. 2009;6(24):99‒117. (in Russ.)
7. Buinevich M.V., Izrailov K.E., Pokusov V.V., Tailakov V.A., Fedulina I.N. An Intelligent Method of Machine Code Algorithmization for Vulnerabilities Search. Zaŝita informacii. Inside. 2020;5(95):57‒63. (in Russ.)
8. Obert J., Loffredo T. Efficient Binary Static Code Data Flow Analysis Using Unsupervised Learning. Proceedings of the 4th International Conference on Artificial Intelligence for Industries, AI4I, 20‒22 September 2021, Laguna Hills, USA). IEEE; 2021. p.89‒90. DOI:10.1109/AI4I51902.2021.00030
9. Jia X., Bin Z., Chao F., Chaojing T. An Automatic Evaluation Approach for Binary Software Vulnerabilities with Address Space Layout Randomization Enabled. Proceedings of the International Conference on Big Data Analysis and Computer Science, BDACS, 25‒27 June 2021, Kunming, China. IEEE; 2021. p.170‒174. DOI:10.1109/BDACS53596.2021.00045
10. Izrailov K.E. Applying of Genetic Algorithms to Decompile Machine Code. Zaŝita informacii. Inside. 2020;3(93):24‒30. (in Russ.)
11. Zaginailo M.V., Fatkhi V.A. Genetic Algorithm as an Effective Tool for Evolutionary Algorithms. Innovatsii. Nauka. Obrazovanie. 2020;22:513‒518. (in Russ.)
12. Maximova E.A. Model of the States of Critical Information Infrastructure Subjects under Destructive Influences in Static Mode. Proc. of Telecom. Universities. 2021;7(3):65‒72. (in Russ.) DOI:10.31854/1813-324X-2021-7-3-65-72
Review
For citations:
Izrailov K. Genetic Decompilation Concept of the Telecommunication Devices Machine Code. Proceedings of Telecommunication Universities. 2021;7(4):95-109. (In Russ.) https://doi.org/10.31854/1813-324X-2021-7-4-95-109