Fuzzy logic based clustering algorithm for management in critical infrastructure

Infrastructure interdependency is a bidirectional interconnection between entities of two infrastructures. These Critical Infrastructures (CIs) suffer from several attacks, vulnerabilities, and failures. Indeed a failure in one CI could lead to serious consequences on physical security, economic security, or public health. However, the protection of these infrastructures is essential. The clustering algorithm is considered as one of the best interesting solutions to reduce its impacts. This paper presents a new approach of the Fuzzy Logic-based clustering algorithm to better identify and understand the overall interconnections between entities in CI. The Fuzzy Logic based on the clustering algorithm is split into Cluster heads (CHs) election and Cluster Members formation (CMs) election. The CH is elected by quantifying the degree of dependency of each component and CM is elected by determining their criticality levels using Failure Mode and Effect Analysis method to determine their Number Priority of Risk. The simulation results demonstrate that by adopting our proposed approach, improved management in CIs is gained not only in enhancing the degree of inter/dependency but also in identifying the criticality of interdependencies, minimizing Round Time Trip of failures nodes detection and reduce uncertainty risks.