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A Vulnerability Assessment Approach for Transportation Networks Subjected to Cyber–Physical Attacks

Author

Listed:
  • Konstantinos Ntafloukas

    (School of Civil Engineering, University College Dublin, D07 R2WY Dublin, Ireland)

  • Liliana Pasquale

    (School of Computer Science, University College Dublin, D07 R2WY Dublin, Ireland)

  • Beatriz Martinez-Pastor

    (School of Civil Engineering, University College Dublin, D07 R2WY Dublin, Ireland)

  • Daniel P. McCrum

    (School of Civil Engineering, University College Dublin, D07 R2WY Dublin, Ireland)

Abstract

Transportation networks are fundamental to the efficient and safe functioning of modern societies. In the past, physical and cyber space were treated as isolated environments, resulting in transportation network being considered vulnerable only to threats from the physical space (e.g., natural hazards). The integration of Internet of Things-based wireless sensor networks into the sensing layer of critical transportation infrastructure has resulted in transportation networks becoming susceptible to cyber–physical attacks due to the inherent vulnerabilities of IoT devices. However, current vulnerability assessment methods lack details related to the integration of the cyber and physical space in transportation networks. In this paper, we propose a new vulnerability assessment approach for transportation networks subjected to cyber–physical attacks at the sensing layer. The novelty of the approach used relies on the combination of the physical and cyber space, using a Bayesian network attack graph that enables the probabilistic modelling of vulnerability states in both spaces. A new probability indicator is proposed to enable the assignment of probability scores to vulnerability states, considering different attacker profile characteristics and control barriers. A probability-based ranking table is developed that details the most vulnerable nodes of the graph. The vulnerability of the transportation network is measured as a drop in network efficiency after the removal of the highest probability-based ranked nodes. We demonstrate the application of the approach by studying the vulnerability of a transportation network case study to a cyber–physical attack at the sensing layer. Monte Carlo simulations and sensitivity analysis are performed as methods to evaluate the results. The results indicate that the vulnerability of the transportation network depends to a large extent on the successful exploitation of vulnerabilities, both in the cyber and physical space. Additionally, we demonstrate the usefulness of the proposed approach by comparing the results with other currently available methods. The approach is of interest to stakeholders who are attempting to incorporate the cyber domain into the vulnerability assessment procedures of their system.

Suggested Citation

  • Konstantinos Ntafloukas & Liliana Pasquale & Beatriz Martinez-Pastor & Daniel P. McCrum, 2023. "A Vulnerability Assessment Approach for Transportation Networks Subjected to Cyber–Physical Attacks," Future Internet, MDPI, vol. 15(3), pages 1-23, February.
  • Handle: RePEc:gam:jftint:v:15:y:2023:i:3:p:100-:d:1083814
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    References listed on IDEAS

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    1. Shin, Jinsoo & Son, Hanseong & Khalil ur, Rahman & Heo, Gyunyoung, 2015. "Development of a cyber security risk model using Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 208-217.
    2. López, Fernando A. & Páez, Antonio & Carrasco, Juan A. & Ruminot, Natalia A., 2017. "Vulnerability of nodes under controlled network topology and flow autocorrelation conditions," Journal of Transport Geography, Elsevier, vol. 59(C), pages 77-87.
    3. Jing Liu & Huapu Lu & Mingyu Chen & Jianyu Wang & Ying Zhang, 2020. "Macro Perspective Research on Transportation Safety: An Empirical Analysis of Network Characteristics and Vulnerability," Sustainability, MDPI, vol. 12(15), pages 1-18, August.
    4. Fotios Zantalis & Grigorios Koulouras & Sotiris Karabetsos & Dionisis Kandris, 2019. "A Review of Machine Learning and IoT in Smart Transportation," Future Internet, MDPI, vol. 11(4), pages 1-23, April.
    5. Zhang, X. & Miller-Hooks, E. & Denny, K., 2015. "Assessing the role of network topology in transportation network resilience," Journal of Transport Geography, Elsevier, vol. 46(C), pages 35-45.
    6. Sheehan, Barry & Murphy, Finbarr & Mullins, Martin & Ryan, Cian, 2019. "Connected and autonomous vehicles: A cyber-risk classification framework," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 523-536.
    7. Taylor, Michael A.P. & Susilawati,, 2012. "Remoteness and accessibility in the vulnerability analysis of regional road networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 761-771.
    8. Daganzo, Carlos F., 1994. "The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory," Transportation Research Part B: Methodological, Elsevier, vol. 28(4), pages 269-287, August.
    9. Gu, Yu & Fu, Xiao & Liu, Zhiyuan & Xu, Xiangdong & Chen, Anthony, 2020. "Performance of transportation network under perturbations: Reliability, vulnerability, and resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    10. Antonio Candelieri & Bruno G. Galuzzi & Ilaria Giordani & Francesco Archetti, 2019. "Vulnerability of public transportation networks against directed attacks and cascading failures," Public Transport, Springer, vol. 11(1), pages 27-49, June.
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