Advertisement

Cyber-Physical System Security

  • Heping Jia
  • Yi DingEmail author
  • Yishuang Hu
  • Yonghua Song
Chapter
  • 28 Downloads

Abstract

The rapid development of advanced information technologies, for example, the Internet of Things and Big Data techniques, has made the energy internet achieve a deep integration of physical systems and cyber systems and realize an effective combination of energy flow and information flow among various networks. However, with increasing automation of the energy internet, the scale of physical networks, the size of cyber networks and the numbers of smart sensors and decision-making units have greatly increased, resulting in complex external or internal factors directly or indirectly impacting the control and decisions of networks through various approaches. The interaction mechanisms between cyber networks and physical networks are becoming increasingly complex in the energy internet, resulting in the security and reliability analysis of cyber-physical systems becoming more complicated. In this chapter, the security of components in cyber-physical systems is first introduced. Multiple uncertainties in cyber-physical system operation are also developed, including different types of cyber attacks and corresponding mitigation strategies as well as the volatility of energy sources and stochastic energy consumption. Moreover, the correlation and cascading failures in cyber-physical systems are analysed to demonstrate the coupling between cyber systems and physical systems. Furthermore, challenges in the security of cyber-physical systems are provided. This chapter mainly analyses cyber-physical system security in the energy internet considering various uncertainties, which can provide technical support for the planning and operation of the energy internet.

Keywords

Cyber-physical system System security Multiple uncertainties Cascading failures 

References

  1. 1.
    A. Humayed, J. Lin, F. Li, B. Luo, Cyber-physical systems security—a survey. IEEE Internet of Things J. 4(6), 1802–1831 (2017)CrossRefGoogle Scholar
  2. 2.
    J. Madden, Security analysis of a cyber physical system: a car example. Missouri University of Science and Technology (2012)Google Scholar
  3. 3.
    Z. Zhang, W. An, F. Shao, Cascading failures on reliability in cyber-physical system. IEEE Trans. Reliab. 65(4), 1745–1754 (2016)CrossRefGoogle Scholar
  4. 4.
    A. Banerjee, K.K. Venkatasubramanian, T. Mukherjee, S.K.S. Gupta, Ensuring safety, security, and sustainability of mission-critical cyber-physical systems. Proc. IEEE 100, 283–299 (2012)CrossRefGoogle Scholar
  5. 5.
    C.W. Ten, C.C. Liu, G. Manimaran, Vulnerability assessment of cybersecurity for SCADA systems. IEEE Trans. Power Syst. 23(4), 1836–1846 (2008)CrossRefGoogle Scholar
  6. 6.
    C.W. Ten, G. Manimaran, C.C. Liu, Cybersecurity for critical infrastructures: Attack and defense modeling. IEEE Trans. Syst. Man Cybern.-Part A: Syst. Hum. 40(4), 853–865 (2010)CrossRefGoogle Scholar
  7. 7.
    S. Sridhar, A. Hahn, M. Govindarasu, Cyber-physical system security for the electric power grid. Proc. IEEE 99(1), 1–15 (2012)Google Scholar
  8. 8.
    D.G. Eliades, M.M. Polycarpou, A fault diagnosis and security framework for water systems. IEEE Trans. Control. Syst. Technol. 18(6), 1254–1265 (2010)CrossRefGoogle Scholar
  9. 9.
    S. Sundaram, C. Hadjicostis, Distributed function calculation via linear iterative strategies in the presence of malicious agents. IEEE Trans. Autom. Control. 56(7), 1495–1508 (2011)MathSciNetzbMATHCrossRefGoogle Scholar
  10. 10.
    F. Pasqualetti, A. Bicchi, F. Bullo, Consensus computation in unreliable networks: A system theoretic approach. IEEE Trans. Autom. Control. 57(1), 90–104 (2012)MathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    R. Akella, H. Tang, B.M. McMillin, Analysis of information flow security in cyber-physical systems. Int. J. Crit. Infrastruct. Prot. 3, 157–173 (2010)CrossRefGoogle Scholar
  12. 12.
    F. Pasqualetti, F. Dörfler, F. Bullo, Attack detection and identification in cyber-physical systems. IEEE Trans. Autom. Control. 58(11), 2715–2729 (2013)MathSciNetzbMATHCrossRefGoogle Scholar
  13. 13.
    S. Amin, A. Cárdenas, S. Sastry, Safe and secure networked control systems under denial-of-service attacks. Hybrid Syst.: Comput. Control. 5469, 31–45 (2009)MathSciNetzbMATHGoogle Scholar
  14. 14.
    Y. Liu, M.K. Reiter, P. Ning, False data injection attacks against state estimation in electric power grids, in Proceedings of ACM Conference Computation Communication Security, Chicago, IL, USA, November 2009 (2009), pp. 21–32Google Scholar
  15. 15.
    A. Teixeira, S. Amin, H. Sandberg, K.H. Johansson, S. Sastry, Cyber security analysis of state estimators in electric power systems, in Proceedings of IEEE Conference Decision Control, Atlanta, GA, USA, December 2010 (2010), pp. 5991–5998Google Scholar
  16. 16.
    Y. Mo, B. Sinopoli, Secure control against replay attacks, in Proceedings Allerton Conference Communication, Control, Computation, Monticello, IL, USA, September 2010 (2010), pp. 911–918Google Scholar
  17. 17.
    A.O. de Sá, L.F.R. Carmo da Costa, R.C. Machado, Covert attacks in cyber-physical control systems. IEEE Trans. Ind. Inf. 13(4), 1641–1651 (2017)CrossRefGoogle Scholar
  18. 18.
    Q. Yan, F.R. Yu, Distributed denial of service attacks in software-defined networking with cloud computing. IEEE Commun. Mag. 53(4), 52–59 (2015)CrossRefGoogle Scholar
  19. 19.
    T.J. Holt, G.W. Burruss, A.M. Bossler, Assessing the macro-level correlates of malware infections using a routine activities framework. Int. J. Offender Ther. Comp. Criminol. 62(6), 1720–1741 (2018)CrossRefGoogle Scholar
  20. 20.
    H. Abualola, H. Alhawai, M. Kadadha, H. Otrok, A. Mourad, An android-based Trojan spyware to study the notification listener service vulnerability. Proc. Comput. Sci. 83, 465–471 (2016)CrossRefGoogle Scholar
  21. 21.
    B. Zhu, A. Joseph, S. Sastry, A taxonomy of cyber attacks on SCADA systems, in 2011 IEEE International Conferences on Internet of Things, and Cyber, Physical and Social Computing, October 2011 (2011), pp. 380–388Google Scholar
  22. 22.
    M. Yasinzadeh, M. Akhbari, Detection of PMU spoofing in power grid based on phasor measurement analysis. IET Gener. Transm. Distrib. 12(9), 1980–1987 (2018)Google Scholar
  23. 23.
    A.F. Taha, J. Qi, J. Wang, J.H. Panchal, Risk mitigation for dynamic state estimation against cyber attacks and unknown inputs. IEEE Trans. Smart Grid 9(2), 886–899 (2018)CrossRefGoogle Scholar
  24. 24.
    A. Farraj, E. Hammad, A.A. Daoud, D. Kundur, A game-theoretic analysis of cyber switching attacks and mitigation in smart grid systems. IEEE Trans. Smart Grid 7(4), 1846–1855 (2016)CrossRefGoogle Scholar
  25. 25.
    C. Kwon, I. Hwang, Cyber attack mitigation for cyber–physical systems: hybrid system approach to controller design. IET Control. Theory Appl. 10(7), 731–741 (2016)Google Scholar
  26. 26.
    P. Srikantha, D. Kundur, A DER attack-mitigation differential game for smart grid security analysis. IEEE Trans. Smart Grid 7(3), 1476–1485 (2016)CrossRefGoogle Scholar
  27. 27.
    X. Liu, Z. Li, Z. Li, Optimal protection strategy against false data injection attacks in power systems. IEEE Trans. Smart Grid 8(4), 1802–1810 (2017)CrossRefGoogle Scholar
  28. 28.
    M. Chlela, D. Mascarella, G. Joós, M. Kassouf, Fallback control for isochronous energy storage systems in autonomous microgrids under denial-of-service cyber-attacks. IEEE Trans. Smart Grid 9(5), 4702–4711 (2018)CrossRefGoogle Scholar
  29. 29.
    V. Matta, M. Di Mauro, M. Longo, DDoS attacks with randomized traffic innovation: botnet identification challenges and strategies. IEEE Trans. Inf. Forensics Secur. 12(8), 1844–1859 (2017)CrossRefGoogle Scholar
  30. 30.
    T.R.B. Kushal, K. Lai, M.S. Illindala, Risk-based mitigation of load curtailment cyber attack using intelligent agents in a shipboard power system. IEEE Trans. Smart Grid.  https://doi.org/10.1109/tsg.2018.2867809
  31. 31.
    C. Foglietta et al., From detecting cyber-attacks to mitigating risk within a hybrid environment. IEEE Syst. J.  https://doi.org/10.1109/jsyst.2018.2824252
  32. 32.
    O. Vukovic, K.C. Sou, G. Dan, H. Sandberg, Network-aware mitigation of data integrity attacks on power system state estimation. IEEE J. Sel. Areas Commun. 30(6), 1108–1118 (2012)CrossRefGoogle Scholar
  33. 33.
    R. Gentz, S.X. Wu, H. Wai, A. Scaglione, A. Leshem, Data injection attacks in randomized gossiping. IEEE Trans. Signal Inf. Process. Over Netw. 2(4), 523–538 (2016)MathSciNetGoogle Scholar
  34. 34.
    P. Lee, A. Clark, L. Bushnell, R. Poovendran, A passivity framework for modeling and mitigating wormhole attacks on networked control systems. IEEE Trans. Autom. Control. 59(12), 3224–3237 (2014)MathSciNetzbMATHCrossRefGoogle Scholar
  35. 35.
    F.F. Wu, P.P. Varaiya, R.S. Hui, Smart grids with intelligent periphery: an architecture for the energy internet. Engineering 1(4), 436–446 (2015)CrossRefGoogle Scholar
  36. 36.
    L. Ju, Z. Tan, J. Yuan, Q. Tan, H. Li, F. Dong, A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response. Appl. Energy 171, 184–199 (2016)CrossRefGoogle Scholar
  37. 37.
    X. Lü, T. Lu, C.J. Kibert, M. Viljanen, Modeling and forecasting energy consumption for heterogeneous buildings using a physical–statistical approach. Appl. Energy 144, 261–275 (2015)CrossRefGoogle Scholar
  38. 38.
    A. Moshari, A. Ebrahimi, M. Fotuhi-Firuzabad, Short-term impacts of DR programs on reliability of wind integrated power systems considering demand-side uncertainties. IEEE Trans. Power Syst. 31(3), 2481–2490 (2016)CrossRefGoogle Scholar
  39. 39.
    H. Jia, Y. Ding, Y. Song, C. Singh, M. Li, Operating reliability evaluation of power systems considering flexible reserve provider in demand side. IEEE Trans. Smart Grid (2018)Google Scholar
  40. 40.
    Q. Tang, K. Yang, D. Zhou, Y. Luo, F. Yu, A real-time dynamic pricing algorithm for smart grid with unstable energy providers and malicious users. IEEE Internet of Things J. 3(4), 554–562 (2016)CrossRefGoogle Scholar
  41. 41.
    H.A. Aalami, S. Nojavan, Energy storage system and demand response program effects on stochastic energy procurement of large consumers considering renewable generation. IET Gener. Transm. Distrib. 10(1), 107–114 (2016)CrossRefGoogle Scholar
  42. 42.
    S. Nojavan, B. Mohammadi-Ivatloo, K. Zare, Optimal bidding strategy of electricity retailers using robust optimisation approach considering time-of-use rate demand response programs under market price uncertainties. IET Gener. Transm. Distrib. 9(4), 328–338 (2015)CrossRefGoogle Scholar
  43. 43.
    M. Marzband, M. Javadi, J.L. Domínguez-García, M.M. Moghaddam, Non-cooperative game theory based energy management systems for energy district in the retail market considering DER uncertainties. IET Gener. Transm. Distrib. 10(12), 2999–3009 (2016)CrossRefGoogle Scholar
  44. 44.
    S. Ali, T.A. Balushi, Z. Nadir, O.K. Hussain, in Cyber Security for Cyber Physical Systems (Springer, Switzerland, 2018)Google Scholar
  45. 45.
    S. Sridhar, A. Hahn, M. Govindarasu, Cyber-physical system security for the electric power grid. Proc. IEEE 100(1), 210–224 (2012)CrossRefGoogle Scholar
  46. 46.
    S.C. Suh, U.J. Tanik, J.N. Carbone, A. Eroglu, Applied Cyber-Physical Systems (Springer, New York, 2014)CrossRefGoogle Scholar
  47. 47.
    S.V. Buldyrev, R. Parshani, G. Paul, H.E. Stanley, S. Havlin, Catastrophic cascade of failures in interdependent networks. Nature 464, 1025–1028 (2010)CrossRefGoogle Scholar
  48. 48.
    S. Corsi, C. Sabelli, General blackout in Italy sunday september 28, 2003, h. 03: 28: 00, in IEEE Power Engineering Society General Meeting, June 2004 (2004), pp. 1691–1702Google Scholar
  49. 49.
    M. Newman, Networks: An Introduction (Oxford University Press, London, 2010)zbMATHCrossRefGoogle Scholar
  50. 50.
    Z. Huang, C. Wang, M. Stojmenovic, A. Nayak, Characterization of cascading failures in interdependent cyber-physical systems. IEEE Trans. Comput. 64(8), 2158–2168 (2015)MathSciNetzbMATHCrossRefGoogle Scholar
  51. 51.
    P. Derler, E.A. Lee, A.S. Vincentelli, Modeling cyber–physical systems. Proc. IEEE 100(1), 13–28 (2012)CrossRefGoogle Scholar
  52. 52.
    F. Zhang, Z. Shi, S. Mukhopadhyay, Robustness analysis for battery-supported cyber-physical systems. ACM Trans. Embed. Comput. Syst. 12(3), 69 (2013)Google Scholar
  53. 53.
    G. Dong, L. Tian, D. Zhou, R. Du, J. Xiao, H.E. Stanley, Robustness of n interdependent networks with partial support-dependence relationship. Europhys. Lett. 105(4), 68004 (2013)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Heping Jia
    • 1
  • Yi Ding
    • 2
    Email author
  • Yishuang Hu
    • 2
  • Yonghua Song
    • 3
  1. 1.School of Economics & ManagementNorth China Electric Power UniversityBeijingChina
  2. 2.College of Electrical EngineeringZhejiang UniversityHangzhouChina
  3. 3.State Key Laboratory of Internet of Things for Smart CityUniversity of MacauMacauChina

Personalised recommendations