Nasrullah Memon

Notice of Violation of IEEE Publication Principles Detecting Critical Regions in Covert Networks: A Case Study of 9/11 Terrorists Network

This paper presents the study of structural cohesion which is discussed in social network analysis (SNA), but can also be used in several other important application areas including investigative data mining for destabilizing terrorist networks. Structural cohesion is defined as the number of actors who, if removed from a group, would disconnect the group. In this paper we discuss structural cohesion concepts, such as cliques, n-cliques, n-clans and k-plex to determine familiarity, robustness and reachability within subgroups of the 9/11 terrorist network. Moreover we also propose a methodology of detecting critical regions in covert networks; removing/capturing those nodes will disrupt most of the network

Structural analysis and mathematical methods for destabilizing terrorist networks using investigative data mining

This paper uses measures of structural cohesion from social network analysis (SNA) literature to discuss how to destabilize terrorist networks by visualizing participation index of various terrorists in the dataset. Structural cohesion is defined as the minimum number of terrorists, who if removed from the group, would disconnect the group. We tested bottom-up measures from SNA (cliques, n-cliques, n-clans and k-plex) using dataset of 9-11 terrorist network, and found that Mohamed Atta, who was known as ring leader of the plot, participated maximum number of groups generated by the structural cohesion measures. n nWe discuss the results of recently introduced algorithms for constructing hierarchy of terrorist networks, so that investigators can view the structure of non-hierarchical organizations, in order to destabilize terrorist networks. Based upon the degree centrality, eigenvector centrality, and dependence centrality measures, a method is proposed to construct the hierarchical structure of complex networks. It is tested on the September 11, 2001 terrorist network constructed by Valdis Krebs. In addition we also briefly discuss various roles in the network i.e., position role index, which discovers various positions in the network, for example, leaders / brokers and followers.

How Investigative Data Mining Can Help Intelligence Agencies to Discover Dependence of Nodes in Terrorist Networks

A new model of dependence centrality is proposed. The centrality measure is based on shortest paths between the pair of nodes. We apply this measure with the demonstration of a small network example. The comparisons are made with betweenness centrality. We discuss how intelligence investigation agencies could benefit from the proposed measure. In addition to that we argue about the investigative data mining techniques we are using, and a comparison is provided with traditional data mining techniques.

Detecting high-value individuals in covert networks: 7/7 London bombing case study

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.

Novel Algorithms for Subgroup Detection in Terrorist Networks

Discovery of the organizational structure of terrorist networks leads investigators to terrorist cells. Therefore, detection of covert networks from terrorists data is important to terrorism investigation and prevention of future terrorist activity. In this paper, we discuss this important area of subgroup detection in terrorist networks, propose novel algorithms for subgroup detection, and present a demonstration system that we have implemented.

Notice of Violation of IEEE Publication Principles Practical Algorithms and Mathematical Models for Destabilizing Terrorist Networks

In this paper we employ practical algorithms and mathematical models for destabilizing terrorist networks. We present two case studies and show how terrorist networks could be destabilized using investigative data mining.

Extracting Information from Semi-structured Web Documents

This article aims to automate the extraction of information from semi-structured web documents by minimizing the amount of hand coding. Extraction of information from the WWW can be used to structure the huge amount of data buried in web documents, so that data mining techniques can be applied. To achieve this target, automated extraction should be utilized to the extent possible since it must keep pace with a dynamic and chaotic Web on which analysis can be carried out using investigative data mining or social network analysis techniques. To achieve that goal a proposed framework called Spiner will be presented and analyzed in this paper.

Retraction Note to: Detecting Hidden Hierarchy in Terrorist Networks: Some Case Studies

The publisher regrets to announce that the following chapter entitled “Detecting Hidden Hierarchy in Terrorist Networks: Some Case Studies” by Nasrullah Memon, Henrik Legind Larsen, David L. Hicks, and Nicholas Harkiolakis, pp. 477-489, published in LNCS 5075 has been retracted. This chapter contains a large amount of reused and uncited material that was not published within quotation marks.

Advanced Web and Network Technologies, and Applications

This article aims to automate the extraction of information from semi-structured web documents by minimizing the amount of hand coding. Extraction of information from the WWW can be used to structure the huge amount of data buried in web documents, so that data mining techniques can be applied. To achieve this target, automated extraction should be utilized to the extent possible since it must keep pace with a dynamic and chaotic Web on which analysis can be carried out using investigative data mining or social network analysis techniques. To achieve that goal a proposed framework called Spiner will be presented and analyzed in this paper.