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Cybersecurity for eMaintenance in railway infrastructure: risks and consequences

Author

Listed:
  • Adithya Thaduri

    (Luleå University of Technology)

  • Mustafa Aljumaili

    (Luleå University of Technology)

  • Ravdeep Kour

    (Luleå University of Technology)

  • Ramin Karim

    (Luleå University of Technology)

Abstract

Recently, due to the advancements in the Information and Communication Technology, there has been lot of emphasis on digitization of the existing and newly developed infrastructure. In transportation infrastructure, in general, 80% of the assets are already in place and there has been tremendous push to move to the digital era. For efficient and effective design, construction, operation and maintenance of the infrastructure, due to this digitization, there is increasing research trend in data-driven decision-making algorithms that are proved to be effective because of several advantages. Since railway is the backbone of the society, the data-driven approaches will ensure the continuous operation, efficient maintenance, planning and potential future investments. The breach and leak of this potential data to the wrong hands might result in havoc, risk, trust, hazards and serious consequences. Hence, the main purpose of this paper is to stress the potential challenges, consequences, threats, vulnerabilities and risk management of data security in the railway infrastructure in context of eMaintenance. In addition, this paper also identifies the research methods to obtain and secure this data for potential possible research.

Suggested Citation

  • Adithya Thaduri & Mustafa Aljumaili & Ravdeep Kour & Ramin Karim, 2019. "Cybersecurity for eMaintenance in railway infrastructure: risks and consequences," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(2), pages 149-159, April.
    • Handle: RePEc:spr:ijsaem:v:10:y:2019:i:2:d:10.1007_s13198-019-00778-w
    DOI: 10.1007/s13198-019-00778-w
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    References listed on IDEAS

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    1. Anna Nagurney & Patrizia Daniele & Shivani Shukla, 2017. "A supply chain network game theory model of cybersecurity investments with nonlinear budget constraints," Annals of Operations Research, Springer, vol. 248(1), pages 405-427, January.
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    Cited by:

    1. Alice Consilvio & José Solís-Hernández & Noemi Jiménez-Redondo & Paolo Sanetti & Federico Papa & Iñigo Mingolarra-Garaizar, 2020. "On Applying Machine Learning and Simulative Approaches to Railway Asset Management: The Earthworks and Track Circuits Case Studies," Sustainability, MDPI, vol. 12(6), pages 1-24, March.
    2. Amit Patwardhan & Adithya Thaduri & Ramin Karim, 2021. "Distributed Ledger for Cybersecurity: Issues and Challenges in Railways," Sustainability, MDPI, vol. 13(18), pages 1-19, September.

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