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Secure synchronization and identification for fractional complex networks with multiple weight couplings under DoS attacks

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Abstract

This paper is concerned with the secure synchronization and topology identification for fractional complex networks (FCNs) with multiple weight couplings under Denial-of-Service (DoS) jamming attacks, where DoS attacks are performed in the controller-to-actuator channels. First, an adaptive topology observer is designed to realize the secure synchronization and topology identification objective. Second, by Lyapunov stability theory and comparison principle, the secure synchronization conditions are achieved. Under the designed observer, the topology identification can be realized, as well. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed scheme and the validity of theoretical results.

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References

  • An XL, Zhang L, Li YZ, Zhang JG (2014) Synchronization analysis of complex networks with multi-weights and its application in public traffic network. Physica A: Stat Mech Appl 412:149–156

  • An XL, Li YZ, Zhang L, Zhang JG, Ma CX (2015) The research on multi-links complex networks and its application in urban public traffic. ICIC Express Lett Part B Appl Int J Res Surv 6:1613–1618

    Google Scholar 

  • Chen X, Zhang J, Ma T (2016) Parameter estimation and topology identification of uncertain general fractional-order complex dynamical networks with time delay. IEEE/CAA J Autom Sin 9(3):295–303

    MathSciNet  Google Scholar 

  • Chen B, Ho DWC, Hu G, Yu L (2018) Secure fusion estimation for bandwidth constrained cyber-physical systems under replay attacks. IEEE Trans Cybern 48(6):1862–1876

    Article  Google Scholar 

  • Cortes J (2008) Discontinuous dynamical systems. IEEE Control Syst Magn 28(3):36–73

    Article  Google Scholar 

  • DeLellis P, di Bernardo M, Russo G (2011) On QUAD. Lipschitz, and contracting vector fields for consensus and synchronization of networks, IEEE Transactions on Circuits and Systems I. 58(3):576–583

    MATH  Google Scholar 

  • Ding D, Wang Z, Ho DWC, Wei G (2017) Observer-based eventtriggering consensus control for multiagent systems with lossy sensors and cyber-attacks. IEEE Trans Cybern 47(8):1936–1947

    Article  Google Scholar 

  • Ding D, Wang Z, Han QL, Wei G (2018) Security control for discrete-time stochastic nonlinear systems subject to deception attacks. IEEE Trans Syst Man Cybern Syst 48(99):779–789

    Article  Google Scholar 

  • Fan YH, Mei J, Liu HM, Fan YL, Liu FX, Zhang YJ (2020) Fast synchronization of complex networks via a periodically intermittent sliding mode control. Neural Process Lett 51:1331–1352

    Article  Google Scholar 

  • Gu Y, Yu Y, Wang H (2017) Synchronization-based parameter estimation of fractional-order neural networks. Phys A 483:351–361

    Article  MathSciNet  Google Scholar 

  • Li RH, Wu HQ, Cao JD (2022) Impulsive exponential synchronization of fractional-order complex dynamical networks with derivative couplings via feedback control based on discrete time state observations. Acta Mathematica Scientia. 42B(2):737–754

    Article  MathSciNet  Google Scholar 

  • Liu D, Ye D (2020) Pinning-observer-based secure synchronization control for complex dynamical networks subject to DoS attacks. IEEE Trans Circ Syst 67(12):5394–5404

    MathSciNet  MATH  Google Scholar 

  • Liu H, Li Y, Li ZY, Lu JA (2021) Topology identification of multilink complex dynamical networks via adaptive observers incorporating chaotic exosignals. IEEE Trans Cybern 99:267–281

    Google Scholar 

  • Lu AY, Yang GH (2018) Input-to-state stabilizing control for cyberphysical systems with multiple transmission channels under denial of service. IEEE Trans Autom Control 63(6):1813–1820

    Article  MathSciNet  Google Scholar 

  • Mannel A, Norelys, Javier A (2015) Using general quadratic Lyapunov functions to prove Lyapunov uniform stability for fractional order systems. Commun Nonlinear Sci Numer Simul 22(3):650–659

  • Mei J, Jiang M, Wang J (2013) Finite-time structure identification and synchronization of drive-response systems with uncertain parameter. Commun Nonlinear Sci Numer Simul 18(4):999–1015

    Article  MathSciNet  Google Scholar 

  • Mirollo R, Strogatz S (1990) Synchronizayion of pulse-coupled biological oscillators. SIAM J Appl Math 50:1645–1662

    Article  MathSciNet  Google Scholar 

  • Papadimitratos P, Fortelle ADL, Evenssen K, Brignolo R, Cosenza S (2009) Vehicular communication systems: enabling technologies, applications, and future outlook on intelligent transportation. Commun Magz IEEE 47(11):84–95

    Article  Google Scholar 

  • Peng X, Wu HQ (2020) Non-fragile robust finite-time stabilization and H infinity performance analysis for fractional-order delayed neural networks with discontinuous activations under the asynchronous switching. Neural Comput Appl 32(8):4045–4071

    Article  Google Scholar 

  • Peng X, Wu HQ, Cao JD (2019) Global nonfragile synchronization in finite time for fractional-order discontinuous neural networks with nonlinear growth activations. IEEE Trans Neural Netw Learn Syst 30(7):2123–2137

    Article  MathSciNet  Google Scholar 

  • Podlubny I (1999) Fractional Differential Equations. Academic, San Diego, CA

    MATH  Google Scholar 

  • Saeedian M, Khalighi M, Azimi-Tafreshi N, Jafari GR, Ausloos M (2017) Memory effects on epidemic evolution: the susceptible-infected-recovered epidemic model. Phys Rev E 95:022409

    Article  MathSciNet  Google Scholar 

  • Shisheh Foroush H, Martnez S (2016) On triggering control of single-input linear systems under pulse-width modulated DoS signals. SIAM J Control Optim 54(6):3084–3105

  • Si G, Sun Z, Zhang H, Zhang Y (2012) Parameter estimation and topology identification of uncertain fractional order complex networks. Commun Nonlinear Sci Numer Simul 17(12):5158–5171

    Article  MathSciNet  Google Scholar 

  • Strogatz SH (2001) Exploring complex networks. Nature 410:268–276

    Article  Google Scholar 

  • Wang XH, Wu HQ, Cao JD (2020) Global leader-following consensus in finite time for fractional-order multiagent systems with discontinuous inherent dynamics subject to nonlinear growth. Nonlinear Anal-Hybrid Syst 37:100888

    Article  MathSciNet  Google Scholar 

  • Wang LH, Mo ZK, Han QL (2020) Secure impulsive Synchronization in lipschitz-type multi-agent systems subject to deception attacks. IEEE J Autom Sin 7(5):1326–1334

    MathSciNet  Google Scholar 

  • Wu X (2008) Synchronization-based topology identification of weighted general complex dynamical networks with time-varying coupling delay. Phys A 387(4):997–1008

    Article  Google Scholar 

  • Wu XJ, Lu HT (2010) Outer synchronization between two different fractional-order general complex dynamical networks. Chin Phys B 19(7):129–140

    Google Scholar 

  • Wu HY, Wang L, Zhao LH, Wang JL (2012) Topology identification of coupled neural networks with multiple weights. Neurocomputing 457(2):254–264

    Google Scholar 

  • Xu LZ (2010) Applied inequalities, Shandong Science and Technology Press

  • Yu D, Righero M, Kocarev L (2006) Estinating topology of networks. Phys Rev Lett 97:31–34

    Google Scholar 

  • Yu J, Cheng H, Jiang HJ (2012) \(\alpha \)-stability and \(\alpha \)-synchronization for fractional-order neural networks. Neural Netw 35:82–87

    Article  Google Scholar 

  • Zhang YQ, Wu HQ, Cao JD (2020) Group consensus in finite time for fractional multiagent systems with discontinuous inherent dynamics subject to Holder growth. IEEE Trans Cybern. https://doi.org/10.1109/TCYB.2020.3023704

  • Zhang TY, Ye D (2020) Distributed secure control against denial-of-service attacks in cyber-physical systems based on K-connected communication topology. IEEE Trans Cybern 50(7):3094–3103

    Article  Google Scholar 

  • Zhang XM, Han QL, Ge X, Ding L (2020) Resilient control design based on a sampled-date model for a class of networked control systems under denial-of-service attacks. IEEE Trans Cybern 50(8):3616–3626

    Article  Google Scholar 

  • Zhang YQ, Wu HQ, Cao JD (2021) Global Mittag–Leffler consensus for fractional singularly perturbed multiagent systems with discontinuous inherent dynamics via event-triggered control strategy. J Frankl Inst 358(3):2086–2114

    Article  Google Scholar 

  • Zhao J, Aziz-Alaoui MA, Bertelle C, Corson N (2016) Sinusoidal disturbance induced topology identification of Hindmarsh–Rose neural networks. Sci Chin Inf Sci 59(11):112205

    Article  Google Scholar 

  • Zhao W, Wu HQ (2018) Fixed-time synchronization of semi-Markovian jumping neural networks with time-verying delays. Adv Differ Equ 2018 (1):213

  • Zheng Y, Wu XQ, Fan ZY, Wang W (2022) Identifying topology and system parameters of fractional-order complex dynamical networks. Appl Math Comput 414:126666

    MathSciNet  MATH  Google Scholar 

  • Zhu S, Zhou J, Chen G, Lu JA (2019) A new method for topology identification of complex dynamical networks. IEEE Trans Cybern 51(4):2224–2231

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Science, Yanshan University, Qinhuangdao, 066001, China

    Jing Bai & Huaiqin Wu

  2. School of Mathematics, Southeast University, Nanjing, 210096, China

    Jinde Cao

  3. Yonsei Frontier Lab, Yonsei University, Seoul, 03722, Korea

    Jinde Cao

Authors
  1. Jing Bai
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  2. Huaiqin Wu
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  3. Jinde Cao
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Correspondence to Huaiqin Wu.

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Communicated by Fabio Durastante.

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This work was supported by Key Project of Natural Science Foundation of China (No. 61833005) and the Natural Science Foundation of China (No. A12171416)

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Bai, J., Wu, H. & Cao, J. Secure synchronization and identification for fractional complex networks with multiple weight couplings under DoS attacks. Comp. Appl. Math. 41, 187 (2022). https://doi.org/10.1007/s40314-022-01895-2

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  • DOI: https://doi.org/10.1007/s40314-022-01895-2

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