Fuzzy Risk Assessment Method for Airborne Network Security Based on AHP-TOPSIS
Kenian Wang1,2,*, Yuan Hong1,2, Chunxiao Li2
1 College of Safety Science and Engineering, Civil Aviation University of China, Tianjin, 300300, China
2 Key Laboratory of Airworthiness Certification Technology for Civil Aviation Aircraft, Civil Aviation University of China, Tianjin, 300300, China
* Corresponding Author: Kenian Wang. Email: 
Computers, Materials & Continua https://doi.org/10.32604/cmc.2024.052088
Received 22 March 2024; Accepted 03 June 2024; Published online 02 July 2024
Abstract
With the exponential increase in information security risks, ensuring the safety of aircraft heavily relies on the accurate performance of risk assessment. However, experts possess a limited understanding of fundamental security elements, such as assets, threats, and vulnerabilities, due to the confidentiality of airborne networks, resulting in cognitive uncertainty. Therefore, the Pythagorean fuzzy Analytic Hierarchy Process (AHP) Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is proposed to address the expert cognitive uncertainty during information security risk assessment for airborne networks. First, Pythagorean fuzzy AHP is employed to construct an index system and quantify the pairwise comparison matrix for determining the index weights, which is used to solve the expert cognitive uncertainty in the process of evaluating the index system weight of airborne networks. Second, Pythagorean fuzzy the TOPSIS to an Ideal Solution is utilized to assess the risk prioritization of airborne networks using the Pythagorean fuzzy weighted distance measure, which is used to address the cognitive uncertainty in the evaluation process of various indicators in airborne network threat scenarios. Finally, a comparative analysis was conducted. The proposed method demonstrated the highest Kendall coordination coefficient of 0.952. This finding indicates superior consistency and confirms the efficacy of the method in addressing expert cognition during information security risk assessment for airborne networks.
Keywords
Airborne networks; information security risk assessment; cognitive uncertainty; Pythagorean fuzzy sets
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