A Distinct Weighted Centrality–RMS Graph Labeling for Cybersecurity Network Prioritization
Graph labeling is a useful way to study the structure of complex networks. In this study, Distinct Weighted Centrality–Root Mean Square Graph Labeling (DWCRMSGL), a method that combines betweenness, degree, and closeness centralities to give unique weighted labels to each vertex is presented. Edge labels using the Root Mean Square (RMS) of the labels of their connected vertices are computed. Also describes an algorithm for this labeling and explain its theoretical properties. Later test the method on the Email-Eu-Core communication network, using the vertex and edge labels to find and rank key users and communication links. This approach allows us to bring together several centrality measures in graph labeling, making it easier to identify important parts of a network. In cybersecurity, this method can help with network monitoring, resource allocation, and assessing communication risks. The labeling is efficient and can be applied to other real-world communication and complex networks.
Keywords: Graph labeling, Network centrality, Betweenness centrality, Root Mean Square (RMS), Email-Eu-Core network, Cybersecurity.
