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CyNetPhy: Towards Pervasive Defense-in-Depth for Smart Grid Security

  • Mohamed AzabEmail author
  • Bassem Mokhtar
  • Mohammed M. Farag
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8985)

Abstract

Security is a major concern in the smart grid technology extensively relying on Information and Communication Technologies (ICT). New emerging attacks show the inadequacy of the conventional defense tools that provision isolated uncooperative services to individual grid components ignoring their real-time dependency and interaction. In this article, we present a smart grid layering model and a matching multi-layer security framework, CyNetPhy, towards enabling cross-layer security of the grid.CyNetPhy tightly integrates and coordinates between a set of interrelated, and highly cooperative real-time defense solutions designed to address the grid security concerns. We advance a high-level overview of CyNetPhy and present an attack scenario against the smart grid supported by a qualitative analysis of the resolution motivating the need to a cross-layer security framework such as CyNetPhy.

Keywords

Smart grid Smart grid security Pervasive monitoring and analysis Autonomic management Elastic computing Privacy-preserving 

Notes

Acknowledgment

This work is supported by the SmartCI Research Center, Alex., Egypt.

References

  1. 1.
    Azab, M., Eltoweissy, M.: Defense as a service cloud for cyber-physical systems. In: 2011 7th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), pp. 392–401. IEEE (2011)Google Scholar
  2. 2.
    Azab, M., Eltoweissy, M.: Bio-inspired evolutionary sensory system for cyber-physical system security. In: Hassanien, A.E., Kim, T.-H., Kacprzyk, J., Awad, A.L. (eds.) Bio-inspiring Cyber Security and Cloud Services: Trends and Innovations. ISRS, vol. 70, pp. 39–69. Springer, Heidelberg (2014)Google Scholar
  3. 3.
    Chen, T.M., Abu-Nimeh, S.: Lessons from stuxnet. Computer 44(4), 91–93 (2011)CrossRefGoogle Scholar
  4. 4.
    Farag, M.M.: Architectural Enhancements to Increase Trust in Cyber-Physical Systems Containing Untrusted Software and Hardware. Ph.D. thesis, Virginia Polytechnic Institute and State University (2012)Google Scholar
  5. 5.
    Huang, Y.F., Werner, S., Huang, J., Kashyap, N., Gupta, V.: State estimation in electric power grids: Meeting new challenges presented by the requirements of the future grid. Signal Process. Mag. IEEE 29(5), 33–43 (2012)CrossRefGoogle Scholar
  6. 6.
    Kopetz, H.: Real-time systems: design principles for distributed embedded applications. Springer, Heidelberg (2011)CrossRefzbMATHGoogle Scholar
  7. 7.
    Liu, Y., Ning, P., Reiter, M.K.: False data injection attacks against state estimation in electric power grids. ACM Trans. Inf. Syst. Secur. (TISSEC) 14(1), 13 (2011)CrossRefGoogle Scholar
  8. 8.
    Mokhtar, B., Eltoweissy, M.: Hybrid intelligence for semantics-enhanced networking operations. In: The Twenty-Seventh International Flairs Conference (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Mohamed Azab
    • 1
    Email author
  • Bassem Mokhtar
    • 2
  • Mohammed M. Farag
    • 2
  1. 1.The City of Scientific Research and Technological ApplicationsAlexandriaEgypt
  2. 2.Electrical Engineering DepartmentAlexandria UniversityAlexandriaEgypt

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