Research on risk propagation method of multimodal transport network under uncertainty

Guo, Jingni; Xu, Junxiang; He, Zhenggang; Liao, Wei

doi:10.1016/j.physa.2020.125494

Cited by 13 publications

(5 citation statements)

References 24 publications

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“…Firstly, since the probability of state U transitioning to state A is obtained according to the negative information function proposed by Ran [29], it has a certain degree of subjectivity. Simulations with real data [31] and improvements to the probability function should be considered. Secondly, the values of parameters in the numerical simulation were set based on the experience summed up in previous research on supply chain risk diffusion [8,9,32], and there is a certain difference from real events.…”

Section: Discussionmentioning

confidence: 99%

Supply Chain Risk Diffusion Model Considering Multi-Factor Influences under Hypernetwork Vision

Wang

et al. 2022

Sustainability

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Considering the problem of risk diffusion in increasingly complex supply chain networks, we propose using the supply chain risk diffusion model, under the hypernetwork vision, to study the influence of certain factors on risk diffusion, including the herd mentality, self-vigilance, talent recruitment, and enterprise management. First of all, the state transition probability tree is constructed to represent the state transition of each enterprise, then the Microscopic Markov Chain Approach (MMCA) is used to analyze the scale of risk spread, and the diffusion threshold of risk is discussed. We find that the herd mentality, self-vigilance, talent recruitment, and enterprise management will effectively curb the spread of risks. Directly recruiting talents and strengthening enterprise management is more effective than increasing vigilance. This study helps professionals to understand the mechanism of risk diffusion, and it provides effective suggestions on how to suppress risk diffusion in the real world.

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Section: Discussionmentioning

confidence: 99%

Supply Chain Risk Diffusion Model Considering Multi-Factor Influences under Hypernetwork Vision

Wang

et al. 2022

Sustainability

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“…Transportation-related risk management research mainly includes supply chain logistics related risks [36][37][38][39], risk assessment of cross-border transport infrastructure projects [40], safety risk assessment based on multimodal transport networks [41], assessing hazmat risk at nodes of transport networks [42], risk propagation method research of multimodal transport networks under uncertainty [43], risk perception in transport [44], cruise ship safety management in Asian regions [45], and cascading failures and attack strategies of multimodal transport networks.…”

Section: Literature Reviewmentioning

confidence: 99%

Resilience Improvement and Risk Management of Multimodal Transport Logistics in the Post–COVID-19 Era: The Case of TIR-Based Sea–Road Multimodal Transport Logistics

2023

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The COVID-19 pandemic has severely impacted international economics and trade, including cargo transportation. As a result, enhancing the resilience of transport and logistics in the post–COVID-19 era has become a general trend. Multimodal transport, with its advantages of speed, large volume and multiple modes, has increasingly gained attention from countries worldwide. However, multimodal transport logistics is a complex and systematic process. Its smooth flow depends not only on the transport itself, but also on the efficient supervision of customs and other government departments at ports. This study employs the theory and method of a super-network to establish a model of multimodal transport logistics, which includes TIR-based sea–road multimodal transport and customs supervision relationships. Structural and resilience-related characteristics of the super-network are analyzed, and performance parameters of the super-network are proposed. A simulation analysis is conducted, and based on the results, countermeasures to improve the resilience and promote risk management of multimodal transport logistics in the post–COVID-19 era are suggested. The findings of this study provide an exploration of more effective ways to ensure the smoothness of multimodal transport logistics and improve system resilience. The study concludes with theoretical and managerial implications.

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“…The risk propagation between CPSs is examined in [16] based on logical equations and using attack trees; the examined relationships are between parent and children nodes. The risk propagation within a transport network under various types of attacks was analyzed in [17], using the percolation theory. The risk and threat propagation in Unmanned Aerial Vehicles and in particular the aggregation process of the threats from the cyber to the physical domain were discussed in [18].…”

Section: Related Workmentioning

confidence: 99%

Attack Path Analysis and Cost-Efficient Selection of Cybersecurity Controls for Complex Cyberphysical Systems

Σπαθούλας

Kavallieratos

Katsikas

et al. 2022

Computer Security. ESORICS 2021 International Workshops

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The increasing integration of information technology with operational technology leads to the formation of Cyber-Physical Systems (CPSs) that intertwine physical and cyber components and connect to each other. This interconnection enables the offering of functionality beyond the combined offering of each individual component, but at the same time increases the cyber risk of the overall system, as such risk propagates between and aggregates at component systems. The complexity of the resulting systems in many cases leads to difficulty in analyzing cyber risk. Additionally, the selection of cybersecurity controls that will effectively and efficiently treat the cyber risk is commonly performed manually, or at best with limited automated decision support. In this paper, we extend our previous work in [1] to analyze attack paths between CPSs on one hand, and we improve the method proposed therein for selecting a set of security controls that minimizes both the residual risk and the cost of implementation. We use the DELTA demand-response management platform for the energy market stakeholders such as Aggregators and Retailers [2] as a use case to illustrate the workings of the proposed approaches. The results are sets of cybersecurity controls applied to those components of the overall system that have been identified to lie in those attack paths that have been identified as most critical among all the identified attack paths.

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Research on risk propagation method of multimodal transport network under uncertainty

Cited by 13 publications

References 24 publications

Supply Chain Risk Diffusion Model Considering Multi-Factor Influences under Hypernetwork Vision

Supply Chain Risk Diffusion Model Considering Multi-Factor Influences under Hypernetwork Vision

Resilience Improvement and Risk Management of Multimodal Transport Logistics in the Post–COVID-19 Era: The Case of TIR-Based Sea–Road Multimodal Transport Logistics

Attack Path Analysis and Cost-Efficient Selection of Cybersecurity Controls for Complex Cyberphysical Systems

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