http://iet.metastore.ingenta.com
1887

Secure estimation for cyber-physical systems under adversarial actuator attacks

Secure estimation for cyber-physical systems under adversarial actuator attacks

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Control Theory & Applications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Almost all of the available literature on secure state estimation focus on sensor attacks. Unlike the existing results, this study investigates the attack-resilient state estimation problem for continuous-time linear systems with sparse actuator attacks and process noises. It is assumed that, the attacker has limited resources and can only manipulate a certain number of actuators. Specifically, a novel switched observer is proposed with milder design conditions which are derived in terms of linear matrix (in)equalities. It is shown that, the observer not only provides an attack-resilient state estimation, but also guarantees that the resulting observer error system is with noise attenuation level which can be optimised. Finally, a simulation example of a linearised reduced-order aircraft system is provided to show the effectiveness of the proposed approach.

References

    1. 1)
      • 1. Pasqualetti, F., Dorfler, F., Bullo, F.: ‘Control-theoretic methods for cyberphysical security: geometric principles for optimal cross-layer resilient control systems’, IEEE Control Syst., 2015, 35, (1), pp. 110127.
    2. 2)
      • 2. Cárdenas, A.A., Amin, S., Sastry, S.: ‘Research challenges for the security of control systems’, Proc. of the 3rd Conf. Hot Topics in Security, 2008.
    3. 3)
      • 3. Wang, D., Wang, Z., Shen, B., et al.: ‘Recent advances on filtering and control for cyber-physical systems under security and resource constraints’, J. Franklin Inst., 2016, 353, (11), pp. 24512466.
    4. 4)
      • 4. Chen, T.M.: ‘Stuxnet, the real start of cyber warfare? [editor's note]’, IEEE Netw., 2010, 24, (6), pp. 23.
    5. 5)
      • 5. Fidler, D.P.: ‘Was stuxnet an act of war? decoding a cyberattack’, IEEE Secur. Privacy, 2011, 9, (4), pp. 5659.
    6. 6)
      • 6. Eldar, Y.C., Kutyniok, G.: ‘Compressed sensing: theory and applications’ (Cambridge University Press, 2012).
    7. 7)
      • 7. Fawzi, H., Tabuada, P., Diggavi, S.: ‘Secure state-estimation for dynamical systems under active adversaries’. Proc. 49th Annual Allerton Conf. Communication, Control, and Computing, September 2011, pp. 337344.
    8. 8)
      • 8. Fawzi, H., Tabuada, P., Diggavi, S.: ‘Secure estimation and control for cyber-physical systems under adversarial attacks’, IEEE Trans. Autom. Control, 2014, 59, (6), pp. 14541467.
    9. 9)
      • 9. Pajic, M., Tabuada, P., Lee, I., et al.: ‘Attack-resilient state estimation in the presence of noise’. Proc. 54th IEEE Conf. Decision and Control, December 2015, pp. 58275832.
    10. 10)
      • 10. Pajic, M., Lee, I., Pappas, G.J.: ‘Attack-resilient state estimation for noisy dynamical systems’, IEEE Trans. Control Netw. Syst., 2017, 4, (1), pp. 8292.
    11. 11)
      • 11. Mo, Y., Sinopoli, B.: ‘Secure estimation in the presence of integrity attacks’, IEEE Trans. Autom. Control, 2015, 60, (4), pp. 11451151.
    12. 12)
      • 12. Han, D., Mo, Y., Xie, L.: ‘Towards a unified resilience analysis: state estimation against integrity attacks’. Proc. 35th Chinese Control Conf., July 2016, pp. 73337340.
    13. 13)
      • 13. Han, D., Mo, Y., Xie, L.: ‘Convex optimization based state estimation against sparse integrity attacks’, arXiv preprint, 2015, arXiv: 1511.07218.
    14. 14)
      • 14. Shoukry, Y., Tabuada, P.: ‘Event-triggered state observers for sparse sensor noise/attacks’, IEEE Trans. Autom. Control, 2016, 61, (8), pp. 20792091.
    15. 15)
      • 15. Shoukry, Y., Nuzzo, P., Puggelli, A., et al.: ‘Secure state estimation for cyber physical systems under sensor attacks: a satisfiability modulo theory approach’, IEEE Trans. Autom. Control, 2017, doi: 10.1109/TAC.2017.2676679.
    16. 16)
      • 16. Chong, M.S., Wakaiki, M., Hespanha, J.P.: ‘Observability of linear systems under adversarial attacks’. Proc. American Control Conf., July 2015, pp. 24392444.
    17. 17)
      • 17. An, L., Yang, G.H.: ‘Secure state estimation against sparse sensor attacks with adaptive switching mechanism’, IEEE Trans. Autom. Control, 2017, submitted for publication.
    18. 18)
      • 18. Lu, A.Y., Yang, G.H.: ‘Secure state estimation for cyber-physical systems under sparse sensor attacks via a switched Luenberger observer’, Inf. Sci., 2017, 417, pp. 454464.
    19. 19)
      • 19. Xie, C.H., Yang, G.H.: ‘Secure estimation for cyber-physical systems with adversarial attacks and unknown inputs: an L2-gain method’, Int. J. Robust Nonlinear Control, 2017, submitted for publication.
    20. 20)
      • 20. Wang, D., Wang, Z., Shen, B., et al.: ‘Security-guaranteed filtering for discrete-time stochastic delayed systems with randomly occurring sensor saturations and deception attacks’, Int. J. Robust Nonlinear Control, 2017, 27, (7), pp. 11941208.
    21. 21)
      • 21. Ding, D., Wang, Z., Daniel, W.C.H., et al.: ‘Distributed recursive filtering for stochastic systems under uniform quantizations and deception attacks through sensor networks’, Atomatica, 2017, 78, pp. 231240.
    22. 22)
      • 22. Ding, D., Wang, Z., Wei, G., et al.: ‘Event-based security control for discrete-time stochastic systems’, IET Control Theory Appl., 2016, 10, (15), pp. 18081815.
    23. 23)
      • 23. Liang, H., Wang, Z., Naeem, W.: ‘Security analysis of stochastic networked control systems under false data injection attacks’, Proc. of the 11th Int. Conf. Control, 2016, pp. 16.
    24. 24)
      • 24. Pasqualetti, F., Dörfler, F., Bullo, F.: ‘Attack detection and identification in cyber-physical systems’, IEEE Trans. Autom. Control, 2013, 58, (11), pp. 27152729.
    25. 25)
      • 25. Miao, F., Zhu, Q., Pajic, M., et al.: ‘Coding schemes for securing cyber-physical systems against stealthy data injection attacks’, IEEE Trans. Control Netw. Syst., 2017, 4, (1), pp. 106117.
    26. 26)
      • 26. Chen, Y., Kar, S., Moura, J.M.F.: ‘Dynamic attack detection in cyber-physical systems with side initial state information’, IEEE Trans. Autom. Control, 2017, 62, (9), pp. 46184624.
    27. 27)
      • 27. Pang, Z.H., Liu, G.P., Zhou, D., et al.: ‘Two-channel false data injection attacks against output tracking control of networked systems’, IEEE Trans. Ind. Electron., 2016, 63, (5), pp. 32423251.
    28. 28)
      • 28. Zhang, R., Venkitasubramaniam, P.: ‘Stealthy control signal attacks in linear quadratic gaussian control systems: detectability reward tradeoff’, IEEE Trans. Inf. Forensics Secur., 2017, 12, (7), pp. 15551570.
    29. 29)
      • 29. Chen, Y., Kar, S., Moura, J.M.F.: ‘Optimal attack strategies subject to detection constraints against cyber-physical systems’, IEEE Trans. Control Netw. Syst., 2017, doi: 10.1109/TCNS.2017.2690399.
    30. 30)
      • 30. Jin, X., Haddad, W.M., Yucelen, T.: ‘An adaptive control architecture for mitigating sensor and actuator attacks in cyber-physical systems’, IEEE Trans. Autom. Control, 2017, doi: 10.1109/TAC.2017.2652127.
    31. 31)
      • 31. Corless, M., Tu, J.: ‘State and input estimation for a class of uncertain systems’, Automatica, 1998, 34, (6), pp. 757764.
    32. 32)
      • 32. Kalsi, K., Lian, J., Hui, S., et al.: ‘Sliding-mode observers for systems with unknown inputs: a high-gain approach’, Automatica, 2010, 46, (2), pp. 347353.
    33. 33)
      • 33. Walcott, B.L.: ‘State observation of nonlinear uncertain dynamical systems’, IEEE Trans. Autom. Control, 1987, 32, (2), pp. 166170.
    34. 34)
      • 34. Hui, S.: ‘Observer design for systems with unknown inputs’, Int. J. Appl. Math. Comput. Sci., 2005, 15, pp. 431446.
    35. 35)
      • 35. Edwards, C., Spurgeon, S.K.: ‘On the development of discontinuous observers’, Int. J. Control, 1994, 59, (5), pp. 12111229.
    36. 36)
      • 36. Cardenas, A.A., Amin, S., Sastry, S.: ‘Secure control: towards survivable cyber-physical systems’. Proc. 28th Int. Conf. Distributed Computing Systems Workshops, June 2008, pp. 495500.
    37. 37)
      • 37. Floquet, T., Edwards, C., Spurgeon, S.K.: ‘On sliding mode observers for systems with unknown inputs’, Int. J. Adapt. Control Signal Process., 2007, 21, (8-9), pp. 638656.
    38. 38)
      • 38. Yang, G.H., Ye, D.: ‘Reliable H control of linear systems with adaptive mechanism’, IEEE Trans. Autom. Control, 2010, 55, (1), pp. 242247.
    39. 39)
      • 39. Liu, M., Ho, D.W., Shi, P.: ‘Adaptive fault-tolerant compensation control for Markovian jump systems with mismatched external disturbance’, Automatica, 2015, 58, pp. 514.
    40. 40)
      • 40. Filippov, A.F.: ‘Differential equations with discontinuous right-hand sides’ (Kluwer Academic Publishers, 1988).
    41. 41)
      • 41. Lu, P., van Kampen, E.J., de Visser, C.C., et al.: ‘Framework for state and unknown input estimation of linear time-varying systems’, Automatica, 2016, 73, pp. 145154.
    42. 42)
      • 42. Siwakosit, W., Hess, R.A.: ‘Multi-input/multi-output reconfigurable flight control design’, J. Guidance Control Dyn., 2001, 24, (6), pp. 10791088.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta.2017.0561
Loading

Related content

content/journals/10.1049/iet-cta.2017.0561
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address