Preview

Scientific and Technical Journal of Information Technologies, Mechanics and Optics

Advanced search

Application of failure detection methods to detect information attacks on the control system

https://doi.org/10.17586/2226-1494-2022-22-3-480-491

Abstract

The problem of ensuring the security of control systems is an important and urgent problem. It consists of eliminating the impact of failures and attacks on control objects and the environment, etc. Prevention of critical failures is important. The purpose of this study is to analyze the similarities between the consequences of attacks on complex technical systems and failures of these systems. In the course of the work, a hypothesis about the similarity of the impact of failures and information attacks on a complex technical system is presented. Both information attacks and failures cause anomalous dynamics of the control object. Analysis of the deviation of the dynamics of the control object from the normal mode of operation will allow us to detect and isolate information attacks and failures. The paper examines the influence of information attacks on the dynamics of automatic control systems. Comparison of abnormal dynamics of control objects during attacks and device failures is carried out. The similarity of the consequences of information attacks and failures of the control system are analyzed, a method for identifying attacks based on the methods developed for detecting failures is developed. Computer modeling of the influence of information attacks and failures on the control system of a DC motor has been carried out. The simulation results allow making a conclusion about the applicability of the failure detection algorithms for detecting attacks. It is shown that failures and information attacks can lead to dangerous consequences for the control system. It seems relevant to study the intersection of the field of information security and failure detection.

About the Authors

A. A. Margun
ITMO University; Institute for Problems in Mechanical Engineering of the Russian Academy of Sciences
Russian Federation

Alexey A. Margun — PhD, Assistant Professor; Researcher

Saint Petersburg, 199178

Saint Petersburg, 199178

sc 55521791600



R. A. Iureva
ITMO University
Russian Federation

Radda A. Iureva — PhD, Associate Professor, Associate Professor

Saint Petersburg, 199178

sc 57190606805



D. V. Kolesnikova
ITMO University
Russian Federation

Daria V. Kolesnikova — PhD Student, Assistant

Saint Petersburg, 199178

sc 57206781641



References

1. Lee J., Bagheri B., Kao H.A. A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manufacturing Letters, 2015, vol. 3, pp. 18–23. https://doi.org/10.1016/j.mfglet.2014.12.001

2. Lasi H., Fettke P., Kemper H.G., Feld T., Hoffmann M. Industry 4.0. Business & Information Systems Engineering, 2014, vol. 6, no. 4, pp. 239–242. https://doi.org/10.1007/s12599-014-0334-4

3. Hwang I., Kim S., Kim Y., Seah C.E. A survey of fault detection, isolation, and reconfiguration methods. IEEE Transactions on Control Systems Technology, 2010, vol. 18, no. 3, pp. 636–653. https://doi.org/10.1109/TCST.2009.2026285

4. Patton R.J., Chen J. On eigenstructure assignment for robust fault diagnosis. International Journal of Robust and Nonlinear Control, 2000, vol. 10, no. 14, pp. 1193–1208. https://doi.org/10.1002/1099-1239(20001215)10:14<1193::AID-RNC523>3.0.CO;2-R

5. Wünnenberg J., Frank P.M. Sensor fault detection via robust observers. System Fault Diagnostics, Reliability and Related Knowledge-Based Approaches. V. 1. Springer, Dordrecht, 1987, pp. 147–160. https://doi.org/10.1007/978-94-009-3929-5_5

6. Watanabe K., Himmelblau D.M. Instrument fault detection in systems with uncertainties. International Journal of Systems Science, 1982, vol. 13, no. 2, pp. 137–158. https://doi.org/10.1080/00207728208926337

7. Frank P.M., Wünnenberg J. Robust fault diagnosis using unknown input observers schemes. Fault Diagnosis in Dynamic Systems: Theory and Application. New York, Prentice-Hall, 1989, pp. 47–98.

8. Gertler J. Fault detection and isolation using parity relations. Control Engineering Practice, 1997, vol. 5, no. 5, pp. 653–661. https://doi.org/10.1016/S0967-0661(97)00047-6

9. Patton R.J., Chen J. Robust fault detection using eigenstructure assignment: A tutorial consideration and some new results. Proc. of

10. Patton R.J., Chen J. Review of parity space approaches to fault diagnosis for aerospace systems. Journal of Guidance, Control, and Dynamics, 1994, vol. 17, no. 2, pp. 278–285. https://doi.org/10.2514/3.21194

11. Stoustrup J., Niemann H.H. Fault estimation — a standard problem approach. International Journal of Robust and Nonlinear Control, 2002, vol. 12, no. 8, pp. 649–673. https://doi.org/10.1002/rnc.716

12. Maqill D.T. Optimal adaptive estimation of sampled stochastic processes. IEEE Transactions on Automatic Control, 1965, vol. 10, no. 4, pp. 434–439. https://doi.org/10.1109/TAC.1965.1098191

13. Maybeck P.S. Stochastic Models, Estimation and Control. V. 1. Arlington, VA, Navtech Press, 1994, 423 p.

14. Maybeck P.S. Stochastic Models, Estimation and Control. V. 2. Arlington, VA, Navtech Press, 1994.

15. Wang H., Lin W. Applying observer based FDI techniques to detect faults in dynamic and bounded stochastic distributions. International Journal of Control, 2000, vol. 73, no. 15, pp. 1424–1436. https://doi.org/10.1080/002071700445433

16. Simani S., Fantuzzi C., Patton R.J. Model-Based Fault Diagnosis in Dynamic Systems Using Identification Techniques. London, U.K., Springer, 2003, XV, 282 p. https://doi.org/10.1007/978-1-4471-3829-7

17. Chen R.H., Ng H.K., Speyer J.L., Guntur L.S., Carpenter R. Health monitoring of a satellite system. Journal of Guidance, Control, and Dynamics, 2006, vol. 29, no. 3, pp. 593–605. https://doi.org/10.2514/1.15012

18. Pertew M., Marquez H.J., Zhao Q. Design of unknown input observers for Lipschitz nonlinear systems. Proceedings of the American Control Conference, 2005, vol. 6, pp. 4198–4203. https://doi.org/10.1109/ACC.2005.1470637

19. Baroni P., Lamperti G., Pogliano P., Zanella M. Diagnosis of a class of distributed discrete-event systems. IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans, 2000, vol. 30, no. 6, pp. 731–752. https://doi.org/10.1109/3468.895897

20. Lunze J., Schröder J. Sensor and actuator fault diagnosis of systems with discrete inputs and outputs. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2004, vol. 34, no. 2, pp. 1096–1107. https://doi.org/10.1109/TSMCB.2003.820593

21. Cordier M.O., Dugue P., Dumas M., Lévy F., Montmain J., Staroswiecki M., Travé Massuyès L. AI and automatic control approaches of model-based diagnosis: Links and underlying hypotheses. IFAC Proceedings Volumes, 2000, vol. 33, no. 11, pp. 279–284. https://doi.org/10.1016/S1474-6670(17)37373-1

22. Cordier M.O., Dague P., Lévy F., Mountmain J., Staroswiecki M., Travé-Massuyès L. Conflicts versus analytical redundancy relations: A comparative analysis of the model based diagnosis approach from the artificial intelligence and automatic control perspectives. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2004, vol. 34, no. 5, pp. 2163–2177. https://doi.org/10.1109/TSMCB.2004.835010

23. Blanke M., Kinnaert M., Lunze J., Staroswiecki M. Diagnosis and Fault-Tolerant Control. Berlin, Springer, 2006, XIX, 672 p. https://doi.org/10.1007/978-3-540-35653-0

24. Zhang Y., Jiang J. Bibliographical review on reconfigurable faulttolerant control systems. Annual Reviews in Control, 2008, vol. 32, no. 2, pp. 229–252. https://doi.org/10.1016/j.arcontrol.2008.03.008

25. Zhang X., Parisini T., Polycarpou M.M. Adaptive fault-tolerant control of nonlinear uncertain systems: an information-based diagnostic approach. IEEE Transactions on Automatic Control, 2004, vol. 49, no. 8, pp. 1259–1274. https://doi.org/10.1109/TAC.2004.832201

26. Iureva R.A., Margun A.A., Maltseva N.K., Vedernikov K. Electromechanical drive fault detection. IOP Conference Series: Materials Science and Engineering, 2019, vol. 643, no. 1, pp. 012114. https://doi.org/10.1088/1757-899X/643/1/012114

27. Zhang Y.M., Jiang J. Active fault-tolerant control system against partial actuator failures. IEE Proceedings: Control Theory and Applications, 2002, vol. 149, no. 1, pp. 95–104. https://doi.org/10.1049/ip-cta:20020110

28. Khurana H., Hadley M., Lu N., Frincke D.A. Smart-grid security issues. IEEE Security and Privacy, 2010, vol. 8, no. 1, pp. 81–85. https://doi.org/10.1109/MSP.2010.49

29. Desnitsky V.A., Levshun D.S., Chechulin A.A., Kotenko I.V. Design technique for secure embedded devices: Application for creation of integrated cyber-physical security system // Journal of Wireless Networks, Ubiquitous Computing, and Dependable Applications, 2016, vol. 7, no. 2, pp. 60–80. https://doi.org/10.22667/JOWUA.2016.06.31.060

30. Alguliyev R., Imamverdiyev Y., Sukhostat L. Cyber-physical systems and their security issues. Computers in Industry, 2018, vol. 100, pp. 212–223. https://doi.org/10.1016/j.compind.2018.04.017

31. Wang E.K., Ye Y., Xu X., Yiu S.M., Hui L.C.K., Chow K.P. Security issues and challenges for cyber physical system. Proc. of the IEEE/ ACM International Conference on Green Computing and Communications (GreenCom), 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, (CPSCom), 2010, pp. 733–738. https://doi.org/10.1109/GreenComCPSCom.2010.36

32. Sicari S., Rizzardi A., Grieco L.A., Coen-Porisini A. Security, privacy and trust in Internet of Things: the road ahead. Computer Networks, 2015, vol. 76, pp. 146–164. https://doi.org/10.1016/j.comnet.2014.11.008

33. Sridhar S., Hahn A., Govindarasu M. Cyber-physical system security for the electric power grid. Proceedings of the IEEE, 2012, vol. 100, no. 1, pp. 210–224. https://doi.org/10.1109/JPROC.2011.2165269

34. Gifty R., Bharathi R., Krishnakumar P. Privacy and security of big data in cyber physical systems using Weibull distribution-based intrusion detection. Neural Computing and Applications, 2019, vol. 31, no. 1, pp. 23–34. https://doi.org/10.1007/s00521-018-3635-6

35. Iureva R.A., Kremlev A.S., Margun A.A., Vlasov S.M., Timko A.S. Measures to design secure cyber-physical things. Smart Innovation, Systems and Technologies, 2019, vol. 142, pp. 315–322. https://doi.org/10.1007/978-981-13-8311-3_27

36. Iureva R.A., Danenkov I.S., Timko A.S., Vlasov S.M., Vasilkov S.D. Optical sensors in IoT. Proceedings of SPIE, 2019, vol. 11028, pp. 1102816. https://doi.org/10.1117/12.2517076

37. Iureva R.A., Belov A.A., Margun A.A., Kremlev A.S. Electric drive attack detection based on state observers. Proc. of the 20th International Carpathian Control Conference (ICCC), 2019, pp. 8766015. https://doi.org/10.1109/carpathiancc.2019.8766015

38. Iureva R., Margun A., Maltseva N., Vedernikov K. Electromechanical drive fault detection. IOP Conference Series: Materials Science and Engineering, 2019, vol. 643, no. 1, pp. 012114. https://doi.org/10.1088/1757-899X/643/1/012114

39. Dobriborsci D., Margun A., Kolyubin S. Theoretical and experimental research of the discrete output robust controller for uncertain plant. Proc. of the 16th European Control Conference (ECC), 2018, pp. 533–538. https://doi.org/10.23919/ECC.2018.8550138

40. Chen J., Patton R.J. Robust Model-Based Fault Diagnosis for Dynamic Systems. Boston, MA, U.S.A., Kluwer Academic Publishers, 1999, pp. 354.

41. Patton R.J., Chen J. Observer-based fault detection and isolation: Robustness and applications. Control Engineering Practice, 1997, vol. 5, no. 5, pp. 671–682. https://doi.org/10.1016/S0967-0661(97)00049-X

42. Isermann R. Supervision, fault-detection and fault-diagnosis methods — An introduction. Control Engineering Practice, 1997, vol. 5, no. 5, pp. 639–652. https://doi.org/10.1016/S0967-0661(97)00046-4

43. Behzad H., Casavola A., Tedesco F., Sadrnia M.A. Fault-tolerant sensor reconciliation schemes based on unknown input observers. International Journal of Control, 2020, vol. 93, no. 3, pp. 669–679. https://doi.org/10.1080/00207179.2018.1484568

44. Morris T., Gao W. Industrial control system cyber attacks. Proc. of the 1st International Symposium for ICS & SCADA Cyber Security Research, 2013, pp. 22–29. https://doi.org/10.14236/ewic/icscsr2013.3

45. Yılmaza E.N., Gönenb S. Attack detection/prevention system against cyber-attack in industrial control systems. Computers and Security, 2018, vol. 77, pp. 94–105. https://doi.org/10.1016/j.cose.2018.04.004

46. Rathika R.K., Marimuthu A. An improved detection and prevention of DDoS attacks in nuclear power plants machine monitoring. Proc. of the Second International Conference on Electrical, Computer and Communication Technologies (ICECCT), 2017, pp. 1–7. https://doi.org/10.1109/ICECCT.2017.8117897

47. Pasqualetti F., Dorfler F., Bullo F. Attack detection and identification in cyber-physical systems. IEEE Transactions on Automatic Control, 2013, vol. 58, no. 11, pp. 2715–2729. https://doi.org/10.1109/TAC.2013.2266831

48. Danenkov I., Kolesnikova D., Babikov A., Iureva R. Security by design development methodology for file hosting case // Smart Innovation, Systems and Technologies, 2020, vol. 188, pp. 383–390. https://doi.org/10.1007/978-981-15-5584-8_33

49. Belov А.А., Aranovskiy S., Ortega R., Barabanov N., Bobtsov А.А. Enhanced parameter convergence for linear systems identification: The DREM approach. Proc. of the 16th European Control Conference (ECC), 2018, pp. 2794–2799. https://doi.org/10.23919/ECC.2018.8550338


Review

For citations:


Margun A.A., Iureva R.A., Kolesnikova D.V. Application of failure detection methods to detect information attacks on the control system. Scientific and Technical Journal of Information Technologies, Mechanics and Optics. 2022;22(3):480-491. https://doi.org/10.17586/2226-1494-2022-22-3-480-491

Views: 11


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2226-1494 (Print)
ISSN 2500-0373 (Online)