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

Abstract

Notice of Violation of IEEE Publication Principles<br><br> "Detecting Critical Regions in Covert Networks: A Case Study of 9/11 Terrorists Networks" <br> by Nasrullah Memon, Kim C. Kristoffersen, David L. Hicks, and Henrik Legind Larsen<br> in the Proceedings of the 11th International Conference on Information Visualization (IV), July 2007<br><br> After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles. <br><br> This paper has copied portions of text from the sources cited below. The lead author, Nasrullah Memon, was found to be solely responsible for the violation. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. <br><br> "Clique Relaxations in Social Network Analysis: The Maximum k-plex Problem"<br> by B. Balasundaram, S. Butenko, I. V. Hicks, S. Sachdeva<br> Posted online, January 2006<br> "Network Analysis of Knowledge Construction in Asynchronous Learning Networks"<br> by Aviv, Reuven; Erlich, Zippy; Ravid, Gilad; Geva, Aviva<br> in the Journal of Asynchronous Learning Networks, Vol 7, No 3, 2003<br><br> <br/> 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