Detecting system faults in hardware and software systems using intelligent solutions
https://doi.org/10.21683/1729-2646-2025-25-4-61-68
Abstract
The paper presents a system for detecting faults in distributed software and hardware systems that is based on a set of intelligent technologies. The method combines dynamic testing (fuzzing) enhanced with large language models, as well as analysis of vulnerability patterns of the well-known MITRE and OWASP knowledge bases to identify software errors that enable potential attacks. The proposed architecture promptly diagnoses failures and faults, localizes their causes and automatically escalates the incident to the system administrator. The practical significance of the solution is confirmed experimentally in terms of such parameters as the average error detection time, code coverage, and the number of detected defects.
About the Authors
I. A. Pankov
Omsk State Technical University
Russian Federation
Russian Federation
Ilia A. Pankov, postgraduate student
Omsk
A. P. Averchenko
Omsk State Technical University
Russian Federation
Russian Federation
Artem P. Averchenko, postgraduate student, OmSTU, head of the Digital Signal Processing using FPGA SDB
Omsk
D. A. Pankov
LANIT-TERKOM LLC
Russian Federation
Russian Federation
Denis A. Pankov, Project Manager and System Analyst, Member of the Program Committee for Information Technology Standardisation, Candidate of Engineering
Saint Petersburg
References
1. Meng R., Mirchev M., Böhme M. et al. Large Language Model guided Protocol Fuzzing. Network and Distributed System Security (NDSS) Symposium 2024; San Diego (CA, USA). DOI: 10.14722/ndss.2024.24556
2. Elnaggar R., Delgado B., Fung J. M. RAG-Based Fuzzing of Cross-Architecture Compilers. (accessed 13.07.2025). Available at: https://arxiv.org/abs/2504.08967.
3. Pankov I.A., Pankov D.A., Denisova L.A. [Automation of development and testing of digital communication systems with multilevel architecture]. Avtomatizatsiya v promyshlennosti 2023;1:31-35. (in Russ.)
4. Pankov I.A., Pankov A.P., Pankov D.A. et al. Prospects for the use of FMEA analyzes for highly critical technical systems. Izvestiya Tula State University 2024;3:26-31. (in Russ.)
5. Pankov I.A. Detecting defects when testing algorithms digital devices based on FPGA. Izvestiya Tula State University 2023;11:277-280. (in Russ.)
6. Pankov D.A., Pankov I.A. Detecting system defects of digital devices in the course of malfunction imitation using fuzzing. Dependability 2023;23(4):51-58. (in Russ.)
7. Chunqiu Steven Xia, Matteo Paltenghi, Jia Le Tian et al. Fuzz4All: Universal Fuzzing with Large Language Models. 2024. (accessed 29.09.2025). Available at: https://arxiv.org/abs/2308.04748.
8. Zafar A., Wajid B., Akram B. A hybrid fault diagnosis architecture for Wireless Sensor Networks. ICOSST; 2015. DOI: 10.1109/ICOSST.2015.7396395
9. Heracleous C., Keliris C., Panayiotou C. et al. Fault diagnosis for a class of nonlinear uncertain hybrid systems. Nonlinear Analysis: Hybrid Systems 2022;44:101137. DOI: 10.1016/j.nahs.2021.101137
10. Pan Z., Fu Y., Guo H. et al. Analysis of Covert Attacks Using False Data against Network Control Systems: Three Case Studies. Syst Sci Complex 2023;36:1407-1422.
11. Reber A., Cha S.K. Optimizing Fuzzing Seed Selection. Proceedings of the 23rd USENIX Security Symposium. San Diego (CA, USA); 2014. Pp. 861-875.
12. Fibich C., Tauner S., Rössler P. et al. FIJI: Fault InJection Instrumenter. EURASIP Journal on Embedded Systems 2019. DOI: 10.1186/s13639-019-0088-7
13. Trippel T., Shin K.G. Fuzzing Hardware as Software. (accessed 13.07.2025). Available at: https://www.usenix.org/system/files/sec22-trippel.pdf
14. Pankov D.A., Denisova L.A. Control and diagnostics of faults in hardware-software complex. Omsk Scientific Bulletin 2018;2(158):128-133. (in Russ.) DOI:https://doi.org/10.25206/1813-8225-2018-158-128-133.
15. Pankov D.A., Denisova L.A. [Designing a software and Hardware system: defining the scope of testing of computer-based devices]. Avtomatrizatsiya v promyshlennosti 2020;12:23-29. (in Russ.)
Review
For citations:
Pankov I.A., Averchenko A.P., Pankov D.A. Detecting system faults in hardware and software systems using intelligent solutions. Dependability. 2025;25(4):61-68. (In Russ.) https://doi.org/10.21683/1729-2646-2025-25-4-61-68
Views:
121
ISSN 1729-2646 (Print)
ISSN 2500-3909 (Online)
ISSN 2500-3909 (Online)
Email this article 