Notice of Violation of IEEE Publication Principles - Detecting high-value individuals in covert networks: 7/7 London bombing case study

Abstract

This article focuses on the study and development of recently introduced new measures, theories, mathematical models and algorithms to detect high value individuals in terrorist networks. Specific models and tools are described, and applied to a case study to demonstrate their applicability to the area. We are confident that the models described can help intelligence agencies in understanding and dealing with terrorist networks.Index Terms -covert networks, detecting hidden hierarchy, high value individuals, position role centrality, social network analysis.

Network analysis of terrorist activities

“…However, the existing researches are limited in the following aspects: Firstly, most of them simply consider the terrorist network as a one-mode network instead of a bipartite network. Even if a bipartite network is built, it is often projected onto a one-mode network for further analysis, with some information lost in the process [15] . Secondly, when analyzing the properties of the network, most of the previous studies focus on topological structures of the networks, while missing the link weight.…”

“…They fail to understand the properties of the networks under study comprehensively and accurately [11][12][13] . Finally, when studying the topological properties, the research is mainly based on the local and macro-scale statistics without the meso-scale measurement of the network, for example, the community structure, which plays an important role in social networks [11,[15][16][17] .…”

“…Previous studies of the terrorist organization network are often conducted from two different perspectives: 1) The personnel perspective: Considering terrorists as vertices, the terrorist network is established according to the relationship between terrorists, and the key persons are identified through network analysis [11][12][13][14][15] ; 2) The organizational perspective: With the terrorist organizations as the vertices, the network is built according to the terrorist activities in a given period of time, and then the key organizations are identified by means of network analysis [16,17] . However, the existing researches are limited in the following aspects: Firstly, most of them simply consider the terrorist network as a one-mode network instead of a bipartite network.…”

A comparative study of social networking approaches in identifying the covert nodes

“…The authors propose a novel explanation mechanism that facilitates verification of the discovered results by generating humanunderstandable natural language explanations describing the unique aspects of these nodes. Nasrullah Memon, Nicholas Harkiolakis and David L. Hicks [21] have introduced the investigative data mining technique to study terrorist networks using descriptive and predictive modeling based on centralities and applied it to the detection of high value individuals by studying the efficiency after removing some nodes, determining how many nodes are dependent on one node and if hidden hierarchy exists find the command structure. The authors have also demonstrated this newly introduced technique with a case study of 7/7 bombing plot.…”

Dominant Features Identification for Covert Nodes in 9/11 Attack Using their Profile

“…This overcomes the issues of the earlier methods like the ensemble problem in which the structural equivalence of the nodes is not efficient enough to determine the key player. Secondly the goal problem where not all the nodes with high centrality values are key players and the distantly connected nodes have less effect on the influential nodes[1] [10].…”