A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 8 Issue 3
Mar.  2021

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 11.8, Top 4% (SCI Q1)
    CiteScore: 17.6, Top 3% (Q1)
    Google Scholar h5-index: 77, TOP 5
Turn off MathJax
Article Contents
Giuseppe Franzè, Francesco Tedesco and Domenico Famularo, "Resilience Against Replay Attacks: A Distributed Model Predictive Control Scheme for Networked Multi-Agent Systems," IEEE/CAA J. Autom. Sinica, vol. 8, no. 3, pp. 628-640, Mar. 2021. doi: 10.1109/JAS.2020.1003542
Citation: Giuseppe Franzè, Francesco Tedesco and Domenico Famularo, "Resilience Against Replay Attacks: A Distributed Model Predictive Control Scheme for Networked Multi-Agent Systems," IEEE/CAA J. Autom. Sinica, vol. 8, no. 3, pp. 628-640, Mar. 2021. doi: 10.1109/JAS.2020.1003542

Resilience Against Replay Attacks: A Distributed Model Predictive Control Scheme for Networked Multi-Agent Systems

doi: 10.1109/JAS.2020.1003542
More Information
  • In this paper, a resilient distributed control scheme against replay attacks for multi-agent networked systems subject to input and state constraints is proposed. The methodological starting point relies on a smart use of predictive arguments with a twofold aim: 1) Promptly detect malicious agent behaviors affecting normal system operations; 2) Apply specific control actions, based on predictive ideas, for mitigating as much as possible undesirable domino effects resulting from adversary operations. Specifically, the multi-agent system is topologically described by a leader-follower digraph characterized by a unique leader and set-theoretic receding horizon control ideas are exploited to develop a distributed algorithm capable to instantaneously recognize the attacked agent. Finally, numerical simulations are carried out to show benefits and effectiveness of the proposed approach.


  • loading
  • [1]
    F. Pasqualetti, R. Carli, and F. Bullo, “A distributed method for state estimation and false data detection in power networks,” in Proc. IEEE Int. Conf. Smart Grid Communications, Brussels, Belgium, 2011, pp. 469–474.
    J. A. Guerrero-Ibanez, S. Zeadally, and J. Contreras-Castillo, “Integration challenges of intelligent transportation systems with connected vehicle, cloud computing, and internet of things technologies,” IEEE Wirel. Commun., vol. 22, no. 6, pp. 122–128, Dec. 2015. doi: 10.1109/MWC.2015.7368833
    A. Teixeira, I. Shames, H. Sandberg, and K. H. Johansson, “A secure control framework for resource-limited adversaries,” Automatica, vol. 51, pp. 135–148, Jan. 2015. doi: 10.1016/j.automatica.2014.10.067
    W. P. M. H. Heemels, A. R. Teel, N. Van de Wouw, and D. Nešić, “Networked control systems with communication constraints: Tradeoffs between transmission intervals, delays and performance,” IEEE Trans. Autom. Control, vol. 55, no. 8, pp. 1781–1796, Aug. 2010. doi: 10.1109/TAC.2010.2042352
    A. A. Cárdenas, S. Amin, and S. Sastry, “Research challenges for the security of control systems,” in Proc. 3rd Conf. Hot Topics in Security, San Jose, USA, 2008.
    W. Lucia, B. Sinopoli, and G. Franzè, “A set-theoretic approach for secure and resilient control of cyber-physical systems subject to false data injection attacks,” in Proc. Science of Security for Cyber-Physical Systems Workshop, Vienna, Austria, 2016, pp. 1–5.
    Q. Y. Zhu, L. Bushnell, and T. Başar, “Resilient distributed control of multi-agent cyber-physical systems,” in Control of Cyber-Physical Systems, D. C. Tarraf, Ed. Heidelberg: Springer, 2013, pp. 301–316.
    Y. P. Guan and X. H. Ge, “Distributed attack detection and secure estimation of networked cyber-physical systems against false data injection attacks and jamming attacks,” IEEE Trans. Signal Inf. Process. Netw., vol. 4, no. 1, pp. 48–59, Mar. 2018.
    D. Zhang, Y. P. Shen, S. Q. Zhou, X. W. Dong, and L. Yu, “Distributed secure platoon control of connected vehicles subject to DoS attack: Theory and application,” IEEE Trans. Syst., Man, Cybernet.: Syst., Feb. 2020. DOI: 10.1109/TSMC.2020.2968606.
    A. Teixeira, S. Amin, H. Sandberg, K. H. Johansson, and S. S. Sastry, “Cyber security analysis of state estimators in electric power systems,” in Proc. 49th IEEE Int. Conf. Decision and Control, Atlanta, USA, 2010, pp. 5991–5998.
    L. Xie, Y. L. Mo, and B. Sinopoli, “ False data injection attacks in electricity markets,” in Proc. 1st IEEE Int. Conf. Smart Grid Communications, Gaithersburg, USA, 2010, pp. 226–231.
    F. Pasqualetti, A. Bicchi, and F. Bullo, “Consensus computation in unreliable networks: A system theoretic approach,” IEEE Trans. Autom. Control, vol. 57, no. 1, pp. 90–104, May 2012. doi: 10.1109/TAC.2011.2158130
    S. Sundaram and C. N. Hadjicostis, “Distributed function calculation via linear iterative strategies in the presence of malicious agents,” IEEE Trans. Autom. Control, vol. 56, no. 7, pp. 1495–1508, Jul. 2011. doi: 10.1109/TAC.2010.2088690
    Y. L. Mo and B. Sinopoli, “Secure control against replay attacks,” in Proc. 47th Annu. Allerton Conf. Communication, Control, and Computing, pp. 911–918, 2009.
    S. Amin, G. A. Schwartz, and S. S. Sastry, “Security of interdependent and identical networked control systems,” Automatica, vol. 49, no. 1, pp. 186–192, Jan. 2013. doi: 10.1016/j.automatica.2012.09.007
    A. Gupta, C. Langbort, and T. Başar, “Optimal control in the presence of an intelligent jammer with limited actions,” in Proc. 49th IEEE Conf. Decision and Control, Atlanta, USA, 2010, pp. 1096–1101.
    W. Chen, D. R. Ding, H. L. Dong, and G. L. Wei, “Distributed resilient filtering for power systems subject to denial-of-service attacks,” IEEE Trans. Syst.,Man,Cybernet.:Syst., vol. 49, no. 8, pp. 1688–1697, Aug. 2019. doi: 10.1109/TSMC.2019.2905253
    M. H. Zhu and S. Martinez, “On distributed constrained formation control in operator–vehicle adversarial networks,” Automatica, vol. 49, no. 12, pp. 3571–3582, Dec. 2013. doi: 10.1016/j.automatica.2013.09.031
    R. Moghadam and H. Modares, “Resilient autonomous control of distributed Multiagent systems in contested environments,” IEEE Trans. Cybernet., vol. 49, no. 11, pp. 3957–3967, Nov. 2019. doi: 10.1109/TCYB.2018.2856089
    P. D. Christofides, R. Scattolini, D. M. de la Peña, and J. F. Liu, “Distributed model predictive control: A tutorial review and future research directions,” Comput. Chem. Eng., vol. 51, pp. 21–41, Apr. 2013. doi: 10.1016/j.compchemeng.2012.05.011
    H. Fawzi, P. Tabuada, and S. Diggavi, “Secure estimation and control for cyber-physical systems under adversarial attacks,” IEEE Trans. Autom. Control, vol. 59, no. 6, pp. 1454–1467, Jun. 2014. doi: 10.1109/TAC.2014.2303233
    P. Velarde, J. M. Maestre, H. Ishii, and R. R. Negenborn, “Scenario-based defense mechanism for distributed model predictive control,” in Proc. IEEE 56th Annu. Conf. Decision and Control, Melbourne, Australia, 2017, pp. 6171–6176.
    A. D. Liu and L. Y. Bai, “Distributed model predictive control for wide area measurement power systems under malicious attacks,” IET Cyber-Phys. Syst.:Theory Appl., vol. 3, no. 3, pp. 111–118, Oct. 2018. doi: 10.1049/iet-cps.2017.0056
    G. Franzè, F. Tedesco, and D. Famularo, “Model predictive control for constrained networked systems subject to data losses,” Automatica, vol. 54, pp. 272–278, Apr. 2015. doi: 10.1016/j.automatica.2015.02.018
    G. Franzè, A. Casavola, D. Famularo, and W. Lucia, “Distributed receding horizon control of constrained networked leader-follower formations subject to packet dropouts,” IEEE Trans. Control Syst. Technol., vol. 26, no. 5, pp. 1798–1809, Sep. 2018. doi: 10.1109/TCST.2017.2723869
    F. Blanchini and S. Miani, Set-Theoretic Methods in Control. 2nd ed. Boston, USA: Birkäuser, 2015.
    S. Bhattacharya, N. Michael, and V. Kumar, “Distributed coverage and exploration in unknown non-convex environments,” in Distributed Autonomous Robotic Systems, A. Martinoli, F. Mondada, N. Correll, G. Mermoud, M. Egerstedt, M. A. Hsieh, L. E. Parker, and K. Støy, Eds. Berlin, Heidelberg: Springer, 2013, pp. 61–75.
    G. Franzè, W. Lucia, and F. Tedesco, “A distributed model predictive control scheme for leader-follower multi-agent systems,” Int. J. Control, vol. 91, no. 2, pp. 369–382, 2018. doi: 10.1080/00207179.2017.1282178
    G. Franzè, F. Tedesco, and W. Lucia, “Resilient control for cyber-physical systems subject to replay attacks,” IEEE Control Syst. Lett., vol. 3, no. 4, pp. 984–989, Oct. 2019. doi: 10.1109/LCSYS.2019.2920507
    D. R. Ding, Z. D. Wang, and Q. L. Han, “A set-membership approach to event-triggered filtering for general nonlinear systems over sensor networks,” IEEE Trans. Autom. Control, vol. 65, no. 4, pp. 1792–1799, Apr. 2020. doi: 10.1109/TAC.2019.2934389


    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索


    Article Metrics

    Article views (1606) PDF downloads(88) Cited by()


    • A first attempt to manage replay attacks in multi-agent systems.
    • Proper formalization to solve constrained regulation problems for LF multi-agent systems.
    • Low-demanding MPC approaches to deal with severe attacks on the communication infrastructure.


    DownLoad:  Full-Size Img  PowerPoint