基于PF-AHP-TOPSIS的机载网络安全模糊风险评估方法

A Fuzzy Risk Assessment Method for Airborne Network Security Based on PF-AHP-TOPSIS

随着信息安全隐患的急剧增加,针对机载网络信息安全问题进行风险评估对保障飞机安全至关重要。然而,由于机载网络的机密性,专家对其资产、威胁、漏洞等基本安全要素的认知不足,存在认知不确定性问题。为此,提出了毕达哥拉斯模糊层次分析逼近理想解排序方法以改善机载网络信息安全风险评估中的专家认知不确定性。首先,采用毕达哥拉斯模糊层次分析法构建风险评估指标体系,用毕达哥拉斯模糊数量化成对比较矩阵以求解指标权重。其次,采用毕达哥拉斯模糊逼近理想解排序法,通过毕达哥拉斯模糊距离测度解模糊实现对机载网络的风险评估。最后,对不同评估方法进行对比分析。经实验验证,所提方法的肯德尔(Kendall)协调系数最大,为0.952,一致性最高,证明方法有效改善了机载网络信息安全风险评估的专家认知不确定性。

With the exponential increase in information security risks,ensuring the safety of aircraft relies heavily on the accurate performance of risk assessment.However,due to the confidentiality of airborne network,experts possess limited understanding of fundamental security elements,such as assets,threats and vulnerabilities,resulting in cognitive uncertainty.Therefore,the Pythagorean Fuzzy Analytic Hierarchy Process-the Technique for Order Preference by Similarity to an Ideal Solution(PF-AHP-TOPSIS)is proposed to address the expert cognitive uncertainty during information security risk assessment for airborne network.Firstly,Pythagorean Fuzzy Analytic Hierarchy Process is employed to construct an index system and quantify the pairwise comparison matrix for determining the index weights.Secondly,PF-AHP-TOPSIS is utilized to assess the risk prioritization of airborne network by using the Pythagorean fuzzy weighted distance measure.Finally,a comparative analysis is conducted.The proposed method demonstrates the highest Kendall coordination coefficient of 0.952,indicating superior consistency and confirming the efficacy of the method in addressing expert cognitive during information security risk assessment for airborne network.