IDEAS home Printed from https://ideas.repec.org/h/zbw/hiclch/209392.html
   My bibliography  Save this book chapter

Cyber-attack impact estimation for a port

In: Digital Transformation in Maritime and City Logistics: Smart Solutions for Logistics. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 28

Author

Listed:
  • König, Sandra
  • Rass, Stefan
  • Schauer, Stefan

Abstract

Purpose: We investigate consequences of a cyber-attack on a port through a simulation model. Motivated by the impact of NotPetya on the container company A.P. Møller-Maersk and the entire supply chain we propose a method to estimate the consequences. Such estimation is a first step towards the identification of protection measures. Methodology: We represent a port as a network of interdependent cyber and physical assets. The operational state of each component is measured on a 3-tier scale and may change due to external problems. The components reaction on security incidents is modeled using Mealy automata. Findings: An implementation of the model as a network of coupled Mealy automata allows simulation of the dynamics after a security incident. This gives an overview on the expected condition of each component over time. The results can be visualized to identify parts that are particularly at danger. Originality: The approach takes into account different kind of information on the cyber and physical system but also learns from past incidents. The automata simulation model provides estimate on the future behavior. Existing data may be used for validation.

Suggested Citation

  • König, Sandra & Rass, Stefan & Schauer, Stefan, 2019. "Cyber-attack impact estimation for a port," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Digital Transformation in Maritime and City Logistics: Smart Solutions for Logistics. Proceedings of the Hamburg International Conference of Logistics, volume 28, pages 164-183, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    • Handle: RePEc:zbw:hiclch:209392
    DOI: 10.15480/882.2496
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/209392/1/hicl-2019-28-164.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.15480/882.2496?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sergey V. Buldyrev & Roni Parshani & Gerald Paul & H. Eugene Stanley & Shlomo Havlin, 2010. "Catastrophic cascade of failures in interdependent networks," Nature, Nature, vol. 464(7291), pages 1025-1028, April.
    2. Panayiotis Kotzanikolaou & Marianthi Theoharidou & Dimitris Gritzalis, 2013. "Assessing n-order dependencies between critical infrastructures," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 9(1/2), pages 93-110.
    3. Ian Dobson & Janghoon Kim & Kevin R. Wierzbicki, 2010. "Testing Branching Process Estimators of Cascading Failure with Data from a Simulation of Transmission Line Outages," Risk Analysis, John Wiley & Sons, vol. 30(4), pages 650-662, April.
    4. Wu, Sheng-Jhih & Chu, Moody T., 2017. "Markov chains with memory, tensor formulation, and the dynamics of power iteration," Applied Mathematics and Computation, Elsevier, vol. 303(C), pages 226-239.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhong, Jilong & Sanhedrai, Hillel & Zhang, FengMing & Yang, Yi & Guo, Shu & Yang, Shunkun & Li, Daqing, 2020. "Network endurance against cascading overload failure," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    2. Stergiopoulos, George & Kotzanikolaou, Panayiotis & Theocharidou, Marianthi & Lykou, Georgia & Gritzalis, Dimitris, 2016. "Time-based critical infrastructure dependency analysis for large-scale and cross-sectoral failures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 12(C), pages 46-60.
    3. Wang, Chengjiang & Wang, Li & Wang, Juan & Sun, Shiwen & Xia, Chengyi, 2017. "Inferring the reputation enhances the cooperation in the public goods game on interdependent lattices," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 18-29.
    4. Tang, Liang & Jing, Ke & He, Jie & Stanley, H. Eugene, 2016. "Robustness of assembly supply chain networks by considering risk propagation and cascading failure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 459(C), pages 129-139.
    5. Shogo Mizutaka & Kousuke Yakubo, 2017. "Structural instability of large-scale functional networks," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-11, July.
    6. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    7. Fridgen, Gilbert & Keller, Robert & Körner, Marc-Fabian & Schöpf, Michael, 2020. "A holistic view on sector coupling," Energy Policy, Elsevier, vol. 147(C).
    8. Hernandez-Fajardo, Isaac & Dueñas-Osorio, Leonardo, 2013. "Probabilistic study of cascading failures in complex interdependent lifeline systems," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 260-272.
    9. Yu, Haitao & Wang, Jiang & Liu, Chen & Deng, Bin & Wei, Xile, 2014. "Delay-induced synchronization transitions in modular scale-free neuronal networks with hybrid electrical and chemical synapses," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 25-34.
    10. Sgrignoli, Paolo & Metulini, Rodolfo & Schiavo, Stefano & Riccaboni, Massimo, 2015. "The relation between global migration and trade networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 245-260.
    11. Zhou, Yaoming & Wang, Junwei, 2018. "Efficiency of complex networks under failures and attacks: A percolation approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 658-664.
    12. Monsalve, Mauricio & de la Llera, Juan Carlos, 2019. "Data-driven estimation of interdependencies and restoration of infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 167-180.
    13. Liu, Huan & Tatano, Hirokazu & Pflug, Georg & Hochrainer-Stigler, Stefan, 2021. "Post-disaster recovery in industrial sectors: A Markov process analysis of multiple lifeline disruptions," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    14. Liu, Run-Ran & Chu, Changchang & Meng, Fanyuan, 2023. "Higher-order interdependent percolation on hypergraphs," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    15. Krawiecki, A., 2018. "Spin glass transition in a simple variant of the Ising model on multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 773-790.
    16. Shekhtman, Louis M. & Danziger, Michael M. & Havlin, Shlomo, 2016. "Recent advances on failure and recovery in networks of networks," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 28-36.
    17. Weihua Lei & Luiz G. A. Alves & Luís A. Nunes Amaral, 2022. "Forecasting the evolution of fast-changing transportation networks using machine learning," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    18. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    19. Leto Peel & Tiago P. Peixoto & Manlio De Domenico, 2022. "Statistical inference links data and theory in network science," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    20. Kyu-Min Lee & Kwang-Il Goh, 2016. "Strength of weak layers in cascading failures on multiplex networks: case of the international trade network," Papers 1603.05181, arXiv.org, revised May 2016.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:hiclch:209392. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://hicl.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.