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Complex cyber-physical networks: From cybersecurity to security control

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Abstract

Complex cyber-physical network refers to a new generation of complex networks whose normal functioning significantly relies on tight interactions between its physical and cyber components. Many modern critical infrastructures can be appropriately modelled as complex cyber-physical networks. Typical examples of such infrastructures are electrical power grids, WWW, public transportation systems, state financial networks, and the Internet. These critical facilities play important roles in ensuring the stability of society as well as the development of economy. Advances in information and communication technology open opportunities for malicious attackers to launch coordinated attacks on cyber-physical critical facilities in networked infrastructures from any Internet-accessible place. Cybersecurity of complex cyber-physical networks has emerged as a hot topic within this context. In practice, it is also very crucial to understand the interplay between the evolution of underlying network structures and the collective dynamics on these complex networks and consequently to design efficient security control strategies to protect the evolution of these networks. In this paper, cybersecurity of complex cyber-physical networks is first outlined and then some security enhancing techniques, with particular emphasis on safety communications, attack detection and fault-tolerant control, are suggested. Furthermore, a new class of efficient secure control strategies are proposed for guaranteeing the achievement of desirable pinning synchronization behaviors in complex cyber-physical networks against malicious attacks on nodes. The authors hope that this paper motivates to design enhanced security strategies for complex cyber-physical network systems, to realize resilient and secure critical infrastructures.

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References

  1. Barabási A L and Albert R, Emergence of scaling in random networks. Science, 1999, 286: 509–512.

    Article  MathSciNet  MATH  Google Scholar 

  2. Strogatz S H, Exploring complex networks. Nature, 2001, 410: 268–276.

    Article  Google Scholar 

  3. Albert R and Barabási A L, Statistical mechanics of complex networks. Rev. Modern Phys., 2002, 74: 47–97.

    Article  MathSciNet  MATH  Google Scholar 

  4. Li X, Jin Y, and Chen G, Complexity and synchronization of the World Trade Web. Physica A, 2003, 328: 287–296.

    Article  MathSciNet  MATH  Google Scholar 

  5. Wen G and Duan Z, Dynamics behaviors of weighted local-world evolving netowrks with extended links. Int. J. Modern Phys. C, 2009, 20: 1719–1735.

    Article  MATH  Google Scholar 

  6. Wen G, Duan Z, Chen G, et al., A weighted local-world evolving network model with aging nodes, Physica A, 2011, 390: 4012–4026.

    Article  Google Scholar 

  7. Wang X and Chen G, Complex networks: Small-world, scale-free and beyond. IEEE Circuits Syst. Mag., 2003, 3: 6–20.

    Article  Google Scholar 

  8. Li X, Wang X, and Chen G, Pinning a complex dynamical network to its equilibrium, IEEE Trans. Circuits Syst. I. Reg. Papers, 2004, 51: 2074–2087.

    Google Scholar 

  9. Lü J and Chen G, A time-varying complex dynamical network model and its controlled synchronization criteria, IEEE Trans. Autom. Control, 2005, 50: 841–846.

    Article  MathSciNet  Google Scholar 

  10. Wang X, Li X, and Lü J, Control and flocking of networked systems via pinning. IEEE Circuits Syst. Mag., 2010, 10: 83–91.

    Article  Google Scholar 

  11. Yu W, Wen G, Yu X, et al., Bridging the gap between complex networks and smart grids, J. Control Decision, 2014, 1: 102–114.

    Article  Google Scholar 

  12. Wen G, Yu W, Hu G, et al., Pinning synchronization of directed networks with switching topologies: A multiple Lyapunov functions approach, IEEE Trans. Neural Netw. Learn. Syst., 2015, 26: 3239–3250.

    Article  MathSciNet  Google Scholar 

  13. Xie L, Mo Y, and Sinopoli B, Integrity data attacks in power market operations. IEEE Trans. Smart Grid, 2011, 2: 659–666.

    Article  Google Scholar 

  14. Das S, Kant K, and Zhang N, Handbook on Securing Cyber-Physical Critical Infrastructure: Foundation and Challenges, Morgan Kaufmann, MA, 2012.

    Google Scholar 

  15. Pasqualetti F, Dorfler F, and Bullo F, Attack detection and identification in cyber-physical systems. IEEE Trans. Autom. Control, 2013, 58: 2715–2729.

    Article  MathSciNet  Google Scholar 

  16. Mo Y, Chabukswar R, and Sinopoli B, Detecting integrity attacks on SCADA systems. IEEE Trans. Control Syst. Technol., 2014, 22: 1396–1407.

    Article  Google Scholar 

  17. Mo Y and Sinopoli B, Secure estimation in the presence of integrity attacks. IEEE Trans. Autom. Control, 2015, 60: 1145–1151.

    Article  MathSciNet  Google Scholar 

  18. Teixeira A, Sou K, Sandberg H, et al., Secure control systems: A quantitative risk management approach, IEEE Control Syst., 2015, 35: 24–45.

    Article  MathSciNet  Google Scholar 

  19. Wen G, Hu G, Hu J, et al., Frequency regulation of source-grid-load systems: A compound control strategy, IEEE Trans. Ind. Informat., 2016, 12: 69–78.

    Google Scholar 

  20. Jeong H, Mason S P, Barabási A L, et al., Lethality and centrality in protein networks. Nature, 2001, 411: 41–42.

    Article  Google Scholar 

  21. Watts D J and Strogatz S H, Collective dynamics of ‘small-world’ networks. Nature, 1998, 393: 440–442.

    Article  Google Scholar 

  22. Albert R, Jeong H, and Barabási A L, Error and attack tolerance of complex networks. Nature, 2000, 406: 378–382.

    Article  Google Scholar 

  23. Motter A E and Lai Y C, Cascade-based attacks on complex networks, Phys. Rev. E, 2002, 66: 065102-1–065102-4.

    Article  Google Scholar 

  24. Albert R, Albert I, and Nakarado G L, Structural vulnerability of the North American power grid. Phys. Rev. E, 2004, 69: 025103-1–025103-4.

    Article  Google Scholar 

  25. Boccaletti S, Buldú J, Criado R, et al., Multiscale vulnerability of complex networks, Chaos, 2007, 17: 043110-1–043110-4.

    Article  MATH  Google Scholar 

  26. Wang J and Rong L, Vulnerability of effective attack on edges in scale-free networks due to cascading failures. Int. J. Mod. Phys. C, 2009, 20: 1291–1298.

    Article  MATH  Google Scholar 

  27. Cyber-physical systems—A concept map. [Online]. Available: http://cyberphysicalsystems.org/.

  28. Yu X, Cecati C, Dillon T, et al., The new frontier of smart grids, IEEE Ind. Electron. Mag., 2011, 5: 49–63.

    Article  Google Scholar 

  29. Dörfler F, Chertkov M, and Bullo F, Synchronization in complex oscillator networks and smart grids. Proc. Natl. Acad. Sci. USA, 2013, 110: 2005–2010.

    Article  MathSciNet  MATH  Google Scholar 

  30. Rohden M, Sorge A, Timme M, et al., Self-organized synchronization in decentralized power grids, Phys. Rev. Lett., 2012, 109: 064101-1–064101-5.

    Article  Google Scholar 

  31. Liu S, Chen B, Zourntos T, et al., A coordinated multi-switch attack for cascading failures in smart grid, IEEE Trans. Smart Grid, 2014, 5: 1183–1195.

    Article  Google Scholar 

  32. Atzori L, Iera A, and Morabito G, The Internet of Things: A survey. Comput. Netw., 2010, 54: 2787–2805.

    Article  MATH  Google Scholar 

  33. Xu L, He W, and Li S, Internet of Things in industries: A survey. IEEE Trans. Ind. Informat., 2014, 10: 2233–2243.

    Article  Google Scholar 

  34. Wang W and Lu Z, Cyber security in the smart grid: Survey and challenges. Comput. Netw., 2013, 57: 1344–1371.

    Article  Google Scholar 

  35. Tan W, Xu K, and Wang D, An anti-tracking source-location privacy protection protocol in WSNs based on path extension. IEEE Internet Things J., 2014, 1: 461–471.

    Article  Google Scholar 

  36. Yu X and Xue Y, Smart grids: A cyber-physical systems perspective. Proc. IEEE, 2016, 104: 1058–1070.

    Article  Google Scholar 

  37. Xu K, Qu Y, and Yang K, A tutorial on the Internet of Things: From a heterogeneous network integration perspective, IEEE Netw., 2016, 30: 102–108.

    Article  Google Scholar 

  38. Petnga L and Xu H, Security of unmanned aerial vehicles: Dynamic state estimation under cyber-physical attacks, Proc. International Conference on Unmanned Aircraft Systems (ICUAS), Arlington, VA USA. Jun. 7–10, 2016, 811–819.

    Google Scholar 

  39. Pasqualetti F, Bicchi A, and Bullo F, Consensus computation in unreliable networks: A system theoretic approach. IEEE Trans. Autom. Control, 2012, 57: 90–104.

    Article  MathSciNet  Google Scholar 

  40. Stuxnet. Available online: https://en.wikipedia.org/wiki/Stuxnet.

  41. Liu Y, Ning P, and Reiter M K, False data injection attacks against state estimation in electric power grids, Proc. 16th ACM Conference on Computer and Communications Security (CCS’09), Chicago, IL. Nov. 9–13, 2009, 21–32.

    Google Scholar 

  42. Roman R, Najera P, and Lopez J, Securing the Internet of Things. Computer, 2011, 44: 51–58.

    Article  Google Scholar 

  43. Wen G, Hu G, Yu W, et al., Consensus tracking for higher-order multi-agents systems with switching directed topologies and occasionally missing control inputs, Syst. Control Lett., 2013, 62: 1151–1158.

    Article  MathSciNet  MATH  Google Scholar 

  44. Khalili M, Zhang X, Polycarpou M, et al., Distributed adaptive fault-tolerant control of uncertain multi-agent systems, Proc. 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, Paris, France, Sept. 2–4, 2015, 66–71.

    Google Scholar 

  45. Mo Y, Weerakkody S, and Sinopoli B, Physical authentication of control systems: Designing watermarked control inputs to detect counterfeit sensor outputs. IEEE Control Syst. Mag., 2015, 35: 93–109.

    Article  MathSciNet  Google Scholar 

  46. Khalili M, Zhang X, Cao Y, et al., Distributed adaptive fault-tolerant control of nonlinear uncertain second-order multi-agent systems, Proc. IEEE 54th Annual Conference on Decision and Control (CDC), Osaka, Japan, Dec. 15–18, 2015, 4480–4485.

    Chapter  Google Scholar 

  47. Feng Z, Hu G, and Wen G, Distributed consensus tracking for multi-agent systems under two types of attacks. Int. J. Robust and Nonlinear Control, 2016, 26: 896–918.

    Article  MathSciNet  MATH  Google Scholar 

  48. Riverso S, Boem F, Ferrari-Trecate G, et al., Plug-and-play fault detection and controlreconfiguration for a class of nonlinear large-scale constrained systems, IEEE Trans. Autom. Control, doi: 10.1109/TAC.2016.2535724.

  49. Boem F, Ferrari R, Keliris C, et al., A distributed networked approach for fault detection of large-scale systems, IEEE Trans. Autom. Control, doi: 10.1109/TAC.2016.2539326.

  50. Feng Z, Wen G, and Hu G, Distributed secure coordinated control for multi-agent systems under strategic attacks, IEEE Trans. Cybern., doi: 10.1109/TCYB.2016.2544062.

  51. Ren W and Beard R W, Consensus seeking in multiagent systems under dynamically changing interaction topologies. IEEE Trans. Autom. Control, 2005, 50: 655–661.

    Article  MathSciNet  Google Scholar 

  52. Poulsen K, Slammer worm crashed Ohio nuke plant network, Available online: http://www. securityfocus.com/news/6767.

  53. NIST framework and roadmap for smart grid interoperability national institute of standards and technology, 2010, Available online: http://www.nist.gov/public affairs/releases/upload/ smartgrid interoperability final.pdf.

  54. Wen G, Duan Z, Su H, et al., A connectivity-preserving flocking algorithm for multi-agent dynamical systems with bounded potential function, IET Control Theory Appl., 2012, 6: 813–821.

    Article  MathSciNet  Google Scholar 

  55. Li Z, Wen G, Duan Z, et al., Designing fully distributed consensus protocols for linear multi-agent systems with directed graphs, IEEE Trans. Autom. Control, 2015, 60: 1152–1157.

    Article  MathSciNet  Google Scholar 

  56. Wen G, Duan Z, Chen G, et al., Consensus tracking of multi-agent systems with Lipschitz-type node dynamics and switching topologies, IEEE Trans. Circuits Syst. I, Reg. Papers, 2014, 61: 499–511.

    Article  MathSciNet  Google Scholar 

  57. Wang Y W, Wang H O, Xiao J W, et al., Synchronization of complex dynamical networks under recoverable attacks, Automatica, 2010, 46: 197–203.

    Article  MathSciNet  MATH  Google Scholar 

  58. Mokhtari G, Nourbakhsh G, and Ghosh A, Smart coordination of energy storage units (ESUs) for voltage and loading management in distribution networks. IEEE Trans. Power Syst., 2013, 28: 4812–4820.

    Article  Google Scholar 

  59. Ermann L, Frahm K, and Shepelyansky D, Google matrix analysis of directed networks. Rev. Mod. Phys., 2015, 87: 1261–1310.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Mathematics, Southeast University, Nanjing, 210096, China

    Guanghui Wen & Wenwu Yu

  2. School of Engineering, RMIT University, Melbourne, VIC, 3001, Australia

    Xinghuo Yu

  3. Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China

    Jinhu Lü

Authors
  1. Guanghui Wen
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  2. Wenwu Yu
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  3. Xinghuo Yu
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  4. Jinhu Lü
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Corresponding author

Correspondence to Guanghui Wen.

Additional information

This paper was supported by the National Key Research and Development Program of China under Grant No. 2016YFB0800401, the National Nature Science Foundation of China under Grant Nos. 61304168, 61673104, and 61322302, the Natural Science Foundation of Jiangsu Province of China under Grant No. BK20130595, the National Ten Thousand Talent Program for Young Top-Notch Talents, the Six Talent Peaks of Jiangsu Province of China under Grant No. 2014-DZXX-004, the Doctoral Program of Higher Education of China under Grant No. 20130092120030, and the Fundamental Research Funds for the Central Universities of China under Grant No. 2242016K41030.

This paper was recommended for publication by Editor SUN Jian.

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Wen, G., Yu, W., Yu, X. et al. Complex cyber-physical networks: From cybersecurity to security control. J Syst Sci Complex 30, 46–67 (2017). https://doi.org/10.1007/s11424-017-6181-x

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  • DOI: https://doi.org/10.1007/s11424-017-6181-x

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