Graph Structural Mining in Terrorist Networks

Authors:
Muhammad Akram Shaikh;Jiaxin Wang;Zehong Yang;Yixu Song
Affiliations:
State Key Lab of Intelligent Technology and Systems, Department of Computer Science & Technology, Tsinghua University, Beijing, P.R. China;State Key Lab of Intelligent Technology and Systems, Department of Computer Science & Technology, Tsinghua University, Beijing, P.R. China;State Key Lab of Intelligent Technology and Systems, Department of Computer Science & Technology, Tsinghua University, Beijing, P.R. China;State Key Lab of Intelligent Technology and Systems, Department of Computer Science & Technology, Tsinghua University, Beijing, P.R. China
Venue:
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Year:
2007

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Abstract

Law enforcement agencies and intelligence analysts frequently face the problems of identifying the actor importance and possible roles among a specific group of entities in a terrorist network. However, such tasks can be fairly time consuming and labor-intensive without the help of some efficient methods. In this paper we will discuss how graph structural mining is applied in the context of terrorist networks using structural measures or properties from social network analysis (SNA) research. Structural properties are determined by the graph structure of the network. These properties are used to evaluate the relationship between entities and identifying different roles. The graph structural mining concept is also demonstrated by using publicly available data on terrorists network in two ways i.e., one for identifying different roles (leaders, brokers, and outliers) known as role structural mining and other for ranking important actors known as rank structural mining. In addition to this we also illustrate how terrorist network is disrupt by knowing the actor importance in a network using rank structural mining.