Skip to main content
Log in

Data Fusion-based resilient control system under DoS attacks: A game theoretic approach

  • Special Section on Advanced Control Theory and Techniques based on Data Fusion
  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

    We’re sorry, something doesn't seem to be working properly.

    Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

Abstract

In this paper, the resilient control under the Denial-of-Service (DoS) attack is rebuilt within the framework of Joint Directors of Laboratories (JDL) data fusion model. The JDL data fusion process is characterized by the so-called Game-in-Game approach, where decisions are made at different layers. The interactions between different JDL levels are considered which take the form of Packet Delivery Rate of the communication channel. Some criterions to judge whether the cyber defense system is able to protect the underlying control system is provided. Finally, a numerical example is proposed to verify the validity of the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. H. C. Cho and K. S. Lee, “Nonlinear networked control systems with random nature using neural approach and dynamic Bayesian networks,” International Journal of Control Automation and Systems, vol. 6, no. 3, pp. 444–452, June 2008.

    Google Scholar 

  2. K. Ji and W. Kim, “Real-time control of networked control systems via Ethernet,” International Journal of Control Automation and Systems, vol. 3, no. 4, pp. 591–600, December 2005.

    Google Scholar 

  3. G. Carl, G. Kesidis, R. R. Brooks, and S. Rai, “Denial-of-service attack-detection techniques,” IEEE Internet Computing Magazine, vol. 10, no. 1, pp. 82–89, February 2006.

    Article  Google Scholar 

  4. Y. L. Huang, A. A. Cardenas, S. Amin, Z. S. Lin, H. Y. Tsai, and S. Sastry, “Understanding the physical and economic consequences of attacks on control systems,” International Journal of Critical Infrastructure Protection, vol. 2, no. 3, pp. 73–83, October 2009.

    Article  Google Scholar 

  5. D. Geer, “Security of critical control systems sparks concern,” Computer, vol. 39, no. 1, pp. 20–23, January 2006.

    Article  MathSciNet  Google Scholar 

  6. C. G. Rieger, D. I. Gertman, and M. A. McQueen, “Resilient control systems: next generation design research,” Proc. of the 2nd Conference on Human System Interactions, Catania, Italy, pp. 629–633, May 2009.

    Google Scholar 

  7. N. A. Giacobe, “Application of the JDL data fusion process model for cyber security,” Proc. SPIE, vol. 7710, 2010.

  8. S. J. Yang, A. Stotz, J. Holsopple, M. Sudit, and M. Kuhl, “High level information fusion for tracking and projection of multistage cyber attacks,” Information Fusion, vol. 10, no. 1, pp. 107–121, January 2009.

    Article  Google Scholar 

  9. Y. Zhang, S. G. Huang, S. Guo, and J. M. Zhu, “Multi-sensor data fusion for cyber security situation awareness,” Procedia Environmental Sciences vol. 10, pp. 1029–1034, September 2011.

    Article  Google Scholar 

  10. H. Yin, L. Wang, and J. Nong, “Survey on gametheoretic information fusion,” Proc. of 7th International Conference on Fuzzy Systems and Knowledge Discovery, Yantai, China, pp. 2147–2151, August 2010.

    Google Scholar 

  11. G. Chen, D. Shen, C. Kwan, J. B. Cruz, and M. Kruger, “Game theoretic approach to threat prediction and situation awareness,” Proc. of 9th International Conference on Information Fusion, Florence, Italy, pp. 1–8, July 2006.

    Google Scholar 

  12. D. Shen, G. Chen, E. Blasch, and T. George, “Adaptive Markov game theoretic data fusion approach for cyber network defense,” Proc. of MILCOM 2007, Orlando, FL, USA, pp. 1–7, October 2007.

    Google Scholar 

  13. D. Shen, G. Chen, J. B. Cruz, and E. Blasch, “A game theoretic data fusion aided path planning approach for cooperative UAV ISR,” Proc. of IEEE Aerospace Conference, Big Sky, USA, pp. 1–9, March 2008.

    Google Scholar 

  14. O. Linda, M. Manic, and T. R. McJunkin, “Anomaly detection for resilient control systems using fuzzy-neural data fusion engine,” Proc. of 4th International Symposium on Resilient Control Systems, Boise, USA, pp. 35–41, August 2011.

    Google Scholar 

  15. T. Basar and P. Bernhard, H Optimal Control and Related Minimax Design Problems: A Dynamic Game Approach, Birkhauser, Boston, MA, 1995.

    Google Scholar 

  16. T. Alpcan and T. Basar, “A game theoretic approach to decision and analysis in network intrusion detection,” Proc. of 42nd IEEE Conference on Decision and Control, Maui, USA, pp. 2595–2600, December 2003.

    Google Scholar 

  17. T. Borgers and R. Sarin, “Learning through reinforcement and replicator dynamics,” Journal of Economic Theory, vol. 77, no. 1, pp. 1–14, November 1993.

    Article  MathSciNet  Google Scholar 

  18. J. S. Shamma and G. Arslan, “Dynamic fictitious play, dynamic gradient play, and distributed convergence to nash equilibria,” IEEE Trans. on Automatic Control, vol. 50, no. 3, pp. 312–327, March 2005.

    Article  MathSciNet  Google Scholar 

  19. Q. Zhu and T. Basar, “Heterogeneous learning in zero-sum stochastic games with incomplete information,” Proc. of 49th IEEE Conference on Decision and Control, Atlanta, USA, pp. 219–224, December 2010.

    Chapter  Google Scholar 

  20. J. Moon and T. Basar, “Control over TCP-like lossy networks: a dynamic game approach,” Proc. of the American Control Conference, Washington, USA, pp. 1578–1583, July 2013.

    Google Scholar 

  21. D. Korzhyk, V. Conitzer, and R. Parr, “Complexity of computing optimal Stackelberg strategies in security resource allocation games,” Proc. of the 24th AAAI Conference on Artificial Intelligence, Georgia, USA, pp. 805–810, July 2010.

    Google Scholar 

  22. Y. Yuan, Q. Zhu, F. C. Sun, Q. Y. Wang, and T. Basar, “Resilient control of cyber-physical systems against denial-of-service attacks,” Proc. of the 6th International Symposium on Resilient Control Systems, San Francisco, USA, pp. 54–59, August 2013.

    Google Scholar 

  23. L. Jiang, W. Yao, Q. H. Wu, J. Y. Wen, and S. J. Cheng, “Delay-dependent stability for load frequency control with constant and time-varying delays,” IEEE Trans. on Power Systems, vol. 27, no. 2, pp. 932–941, July 2009.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yuan Yuan.

Additional information

Yuan Yuan received his B.S. degree in Electrical Engineering from Beihang University, Beijing, China, in 2009. He received his Ph.D. degree in Computer Science and Technology from Tsinghua University, Beijing, China. His main research interests include robust control/filter theory, security of cyber-physical system and networked control systems.

Fuchun Sun received his B.S. and M.S. degrees from the Naval Aeronautical Engineering Academy, Yantai, China, in 1986 and 1989, respectively, and his Ph.D. degree from Tsinghua University, Beijing, China, in 1998. He is currently a professor with the Department of Computer Science and Technology, Tsinghua University. His research interests include intelligent control and robotics.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yuan, Y., Sun, F. Data Fusion-based resilient control system under DoS attacks: A game theoretic approach. Int. J. Control Autom. Syst. 13, 513–520 (2015). https://doi.org/10.1007/s12555-014-0316-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-014-0316-9

Keywords

Navigation