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A control system testbed to validate critical infrastructure protection concepts

Author

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  • Morris, Thomas
  • Srivastava, Anurag
  • Reaves, Bradley
  • Gao, Wei
  • Pavurapu, Kalyan
  • Reddi, Ram

Abstract

This paper describes the Mississippi State University SCADA Security Laboratory and Power and Energy Research laboratory. This laboratory combines model control systems from multiple critical infrastructure industries to create a testbed with functional physical processes controlled by commercial hardware and software over common industrial control system routable and non-routable networks. Laboratory exercises, functional demonstrations, and lecture material from the testbed have been integrated into a newly developed industrial control system cybersecurity course, into multiple other engineering and computer science courses, and into a series of short courses targeted to industry. Integration into the classroom allows the testbed to provide a workforce development function, prepares graduate students for research activities, and raises the profile of this research area with students. The testbed enables a research process in which cybersecurity vulnerabilities are discovered, exploits are used to understand the implications of the vulnerability on controlled physical processes, identified problems are classified by criticality and similarities in type and effect, and finally cybersecurity mitigations are developed and validated against within the testbed. Overviews of research enabled by the testbed are provided, including descriptions of software and network vulnerability research, a description of forensic data logger capability developed using the testbed to retrofit existing serial port MODBUS and DNP3 devices, and a description of intrusion detection research which leverages unique characteristics of industrial control systems.

Suggested Citation

  • Morris, Thomas & Srivastava, Anurag & Reaves, Bradley & Gao, Wei & Pavurapu, Kalyan & Reddi, Ram, 2011. "A control system testbed to validate critical infrastructure protection concepts," International Journal of Critical Infrastructure Protection, Elsevier, vol. 4(2), pages 88-103.
  • Handle: RePEc:eee:ijocip:v:4:y:2011:i:2:p:88-103
    DOI: 10.1016/j.ijcip.2011.06.005
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    Citations

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    Cited by:

    1. Berghout, Tarek & Benbouzid, Mohamed & Muyeen, S.M., 2022. "Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects," International Journal of Critical Infrastructure Protection, Elsevier, vol. 38(C).
    2. Singh, Abhishek Narain & Gupta, M.P. & Ojha, Amitabh, 2014. "Identifying critical infrastructure sectors and their dependencies: An Indian scenario," International Journal of Critical Infrastructure Protection, Elsevier, vol. 7(2), pages 71-85.
    3. Vosughi, Amirkhosro & Tamimi, Ali & King, Alexandra Beatrice & Majumder, Subir & Srivastava, Anurag K., 2022. "Cyber–physical vulnerability and resiliency analysis for DER integration: A review, challenges and research needs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    4. Knowles, William & Prince, Daniel & Hutchison, David & Disso, Jules Ferdinand Pagna & Jones, Kevin, 2015. "A survey of cyber security management in industrial control systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 9(C), pages 52-80.
    5. Wang, Wu & Harrou, Fouzi & Bouyeddou, Benamar & Senouci, Sidi-Mohammed & Sun, Ying, 2022. "Cyber-attacks detection in industrial systems using artificial intelligence-driven methods," International Journal of Critical Infrastructure Protection, Elsevier, vol. 38(C).
    6. Al-Daweri, Muataz Salam & Abdullah, Salwani & Ariffin, Khairul Akram Zainol, 2021. "A homogeneous ensemble based dynamic artificial neural network for solving the intrusion detection problem," International Journal of Critical Infrastructure Protection, Elsevier, vol. 34(C).
    7. Urrea, Claudio & Morales, Claudio & Kern, John, 2016. "Implementation of error detection and correction in the Modbus-RTU serial protocol," International Journal of Critical Infrastructure Protection, Elsevier, vol. 15(C), pages 27-37.
    8. Bjorn Vaagensmith & Vivek Kumar Singh & Robert Ivans & Daniel L. Marino & Chathurika S. Wickramasinghe & Jacob Lehmer & Tyler Phillips & Craig Rieger & Milos Manic, 2021. "Review of Design Elements within Power Infrastructure Cyber–Physical Test Beds as Threat Analysis Environments," Energies, MDPI, vol. 14(5), pages 1-24, March.
    9. Umer, Muhammad Azmi & Junejo, Khurum Nazir & Jilani, Muhammad Taha & Mathur, Aditya P., 2022. "Machine learning for intrusion detection in industrial control systems: Applications, challenges, and recommendations," International Journal of Critical Infrastructure Protection, Elsevier, vol. 38(C).
    10. Ndonda, Gorby Kabasele & Sadre, Ramin, 2020. "Network trace generation for flow-based IDS evaluation in control and automation systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 31(C).

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