Using Mathematical Models in Decision Making Methodologies to Find Key Nodes in the Noordin Dark Network

Abstract

A Dark Network is a network that cannot be accessed through tradition means. Once uncovered, to any degree, dark network analysis can be accomplished using the SNA software. The output of SNA software includes many measures and metrics. For each of these measures and metric, the output in ORA additionally provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning best methods to disrupt or deceive a given dark network. In the Noordin Dark network, different nodes were identified as key nodes based upon the metric used. Our goal in this paper is to use methodologies to identify the key players or nodes in a Dark Network in a similar manner as we previously proposed in social networks. We apply two multi-attribute decision making methods, a hybrid AHP & TOPSIS and an average weighted ranks scheme, to analyze these outputs to find the most influential nodes as a function of the decision makers' inputs. We compare these methods by illustration using the Noordin Dark Network with seventy-nine nodes. We discuss sensitivity analysis that is applied to the criteria weights in order to measure the change in the ranking of the nodes.

An Alternative Approach to the Lottery Method in Utility Theory for Game Theory

“…AHP and AHP-TOPSIS hybrids have been used to rank order alternatives among numerous criteria in many areas of research in business industry, and government including such areas as social networks [2] [3], dark networks [4], terrorist phase planning [5] [6], and terrorist targeting [7].…”

An Innovative Approach for Identification of Pivotal node in Terrorist Network using TOPSIS Method (An Anti-Terrorism approach)

“…A mechanism for subgroup detection and terrorist agility analysis is created by Memon and co-authors in literature [7]. To find the order of a group and the master of the group the techniques make use of centrality measures as well as data mining techniques with mathematical model for the finding of mater nodes in the network were used by Fox and co-authors in [16]. Methods for the ranking of each node and determination of the most important path in the network are suggested in [15].…”

An innovative approach for identification of pivotal node in terrorist network using promethee method (an anti-terrorism approach)

“…The techniques make also use of centrality measures combined with data mining techniques to find the hierarchy of a group and the leader of the group. Fox and co-authors to have employed hybrid AHP and TOPSIS methods for the identification of key nodes in the network in [16].Also, recent works like [15] have suggested methods for the ranking of each node and determination of the most important path through the network. PROMETHEE was presented by J.P. Brans in 1982 [10].…”