Advertisement

Toward the Science of Industrial Control Systems Security and Resiliency

  • Mohammad Ashiqur RahmanEmail author
  • Ehab Al-ShaerEmail author
Chapter
Part of the Advances in Information Security book series (ADIS, volume 75)

Abstract

The supervisory control and data acquisition (SCADA) system is the major industrial control system (ICS), which is responsible for collecting data from end devices, analyzing data, and managing the system efficiently by sending necessary control commands to the corresponding end devices. Unlike traditional cyber networks, a SCADA system consists of heterogeneous devices that communicate with one another under various communication protocols, physical media, and security properties. Failures or attacks on such networks have the potential of data unavailability and false data injection causing incorrect system estimations and control decisions leading to non-optimal management or critical damages of the system. This chapter provides a theoretical baseline for assessing the security and resiliency of ICS by presenting two formal frameworks, one for security analysis and one for resiliency analysis, considering smart grid SCADA systems. These frameworks take smart grid configurations and organizational security or resiliency requirements as inputs, formally model configurations and various security properties, and verify the dependability of the system under potential attacks or contingencies. The execution of each of these frameworks is demonstrated on an example case study.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    A.J. Wood, B.F. Wollenberg, Power Generation, Operation, and Control, 2nd edn. (Wiley, New York, 1996)Google Scholar
  2. 2.
    A. Abur, A.G. Exposito, Power System State Estimation: Theory and Implementation (CRC Press, New York, 2004)CrossRefGoogle Scholar
  3. 3.
    Nistir 7628: Guidelines for smart grid cyber security. (Smart Grid Interoperability Panel- Cyber Security Working Group, Aug 2010), http://www.nist.gov/smartgrid/upload/nistir-7628_total.pdf
  4. 4.
    M.A. Rahman, E. Al-Shaer, R. Kavasseri. Security threat analytics and countermeasure synthesis for state estimation in smart power grids. In IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), June 2014Google Scholar
  5. 5.
    M.A. Rahman, E. Al-Shaer, R. Kavasseri. Impact analysis of topology poisoning attacks on economic operation of the smart power grid. In International Conference on Distributed Computing Systems (ICDCS), July 2014Google Scholar
  6. 6.
    M.A. Rahman, A.H.M. Jakaria, E. Al-Shaer. Formal analysis for dependable supervisory control and data acquisition in smart grids. In IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), June 2016Google Scholar
  7. 7.
    L. de Moura, N. Bjørner. Satisfiability modulo theories: An appetizer. In Brazilian Symposium on Formal Methods, 2009Google Scholar
  8. 8.
    Y. Liu, P. Ning, M. Reiter. False data injection attacks against state estimation in electric power grids. In ACM Conference on Computer and Communications Security (CCS), pp. 21–32, Nov 2009Google Scholar
  9. 9.
    A. Monticelli, State Estimation in Electric Power Systems: A Generalized Approach (Kluwer Academic Publishers, Norwell, 1999)CrossRefGoogle Scholar
  10. 10.
    Z3: Theorem prover. (Microsoft Research, 2013), http://research.microsoft.com/en-us/um/redmond/projects/z3/
  11. 11.
    Power systems test case archive. http://www.ee.washington.edu/research/pstca/
  12. 12.
    National Institute of Standards and Technology. U.S. Department of Commerce. http://www.nist.gov/, http://www.nist.gov/publication-portal
  13. 13.
    North American Electric Reliability Corporation. http://www.nerc.com, http://www.nerc.com/pa/Stand/Pages/default.aspx

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Florida International UniversityMiamiUSA
  2. 2.University of North Carolina at CharlotteCharlotteUSA

Personalised recommendations