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The article presents an approach to the strategic analysis of information security of transport and logistics centers (TLCs). The proposed method is based on expert assessments of the factors that determine the level of TLC IS risk. Strategic analysis is the basis of a decision support system for ensuring an appropriate level of TLC security. It is based on the tools of fuzzy set theory: Linguistic assessments of the factors influencing the information security risk using triangular membership functions; Fuzzy Analytic Hierarchy Process (AHP) method to determine the fuzzy importance coefficients of the factors and subfactors of the proposed model; Center of Area (CoA) method to defuzzify fuzzy triangular values; Fuzzy Simple Additive Weighting (SAW) method to rank the TLC IS risk factors and select an effective strategic solution. For the strategic analysis of the TLC IS status, an extended and modified informative matrix was used to assets the status of the Wilson system. The developed model for assessing the level of TLC IS risk will ensure the implementation of effective strategies to ensure it. The model is implemented in the Python programming language. Further research is seen in the implementation of the proposed model in the decision support system for the management TLC IS.

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Simulation of Strategies for Providing Information Security of the Transport and Logistics Center Based on Fuzzy Logic Methods

  • 会议论文

  • 发表日期：

    2025年

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  • Oleksii Trunov,
  • Mariia Dorosh,
  • Igor Skiter,
  • Elena Trunova,
  • Mariia Voitsekhovska

摘要

The article presents an approach to the strategic analysis of information security of transport and logistics centers (TLCs). The proposed method is based on expert assessments of the factors that determine the level of TLC IS risk. Strategic analysis is the basis of a decision support system for ensuring an appropriate level of TLC security. It is based on the tools of fuzzy set theory: Linguistic assessments of the factors influencing the information security risk using triangular membership functions; Fuzzy Analytic Hierarchy Process (AHP) method to determine the fuzzy importance coefficients of the factors and subfactors of the proposed model; Center of Area (CoA) method to defuzzify fuzzy triangular values; Fuzzy Simple Additive Weighting (SAW) method to rank the TLC IS risk factors and select an effective strategic solution. For the strategic analysis of the TLC IS status, an extended and modified informative matrix was used to assets the status of the Wilson system. The developed model for assessing the level of TLC IS risk will ensure the implementation of effective strategies to ensure it. The model is implemented in the Python programming language. Further research is seen in the implementation of the proposed model in the decision support system for the management TLC IS.