detectVNs: Detects vulnerable nodes (VNs) based on five-point summary of...
In kr-swapnil/NetVA: An R package for network vulnerability and influence analysis

detectVNs

R Documentation

Detects vulnerable nodes (VNs) based on five-point summary of boxplot

Description

This function detects vulnerable nodes (VNs) based on five-point summary of boxplot. It takes first input a numeric vector of topological values for all nodes; whereas, second input is a keyword for topological property based on which users want to identify VNs.

Usage

detectVNs(v, t, p)

Arguments

`v`	Character vector containing names for all nodes of the given network.
`t`	Numeric vector containing values of one topological property for all nodes of the given network. Where, the length of v and t should be equal. Note: v and t should be in the same order i.e. position of one particular node in v and position of value of topological property for that node in t should be the same.
`p`	Case sensitive. Keyword for topological property based on which users want to identify VNs. Keyword should be one from the following keywords: ACC (Average closeness), ANC (Average node connectivity), NDE (Network density), NCE (Network centralization), APL (Average path length), ABC (Average betweenness), APN (Articulation point), NDI (Network diameter), CCO (Clustering coefficient), GEF (Global efficiency), COH (Cohesiveness), COM (Compactness), AEC (Average eccentricity), and HET (Heterogeneity).

Details

Different keywords for fourteen topological properties implemented in NetVA current version are as follows: ANC (Average node connectivity), NDE (Network density), NCE (Network centralization), APL (Average path length), ABC (Average betweenness), ACC (Average closeness), APN (Articulation point), NDI (Network diameter), CCO (Clustering coefficient), GEF (Global efficiency), COH (Cohesiveness), COM (Compactness), AEC (Average eccentricity), and HET (Heterogeneity).