DocumentCode
2416374
Title
Notice of Violation of IEEE Publication Principles
Detecting Critical Regions in Covert Networks: A Case Study of 9/11 Terrorists Network
Author
Memon, Nasrullah ; Kristoffersen, Kim C. ; Hicks, David L. ; Larse, Henrik Legind
Author_Institution
Dept. of Comput. Sci. & Eng., Aalborg Universitet, Esbjerg
fYear
2007
fDate
10-13 April 2007
Firstpage
861
Lastpage
870
Abstract
Notice of Violation of IEEE Publication Principles
"Detecting Critical Regions in Covert Networks: A Case Study of 9/11 Terrorists Networks"
by Nasrullah Memon, Kim C. Kristoffersen, David L. Hicks, and Henrik Legind Larsen
in the Proceedings of the 11th International Conference on Information Visualization (IV), July 2007
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.
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.
"Clique Relaxations in Social Network Analysis: The Maximum k-plex Problem"
by B. Balasundaram, S. Butenko, I. V. Hicks, S. Sachdeva
Posted online, January 2006
"Network Analysis of Knowledge Construction in Asynchronous Learning Networks"
by Aviv, Reuven; Erlich, Zippy; Ravid, Gilad; Geva, Aviva
in the Journal of Asynchronous Learning Networks, Vol 7, No 3, 2003
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
"Detecting Critical Regions in Covert Networks: A Case Study of 9/11 Terrorists Networks"
by Nasrullah Memon, Kim C. Kristoffersen, David L. Hicks, and Henrik Legind Larsen
in the Proceedings of the 11th International Conference on Information Visualization (IV), July 2007
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.
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.
"Clique Relaxations in Social Network Analysis: The Maximum k-plex Problem"
by B. Balasundaram, S. Butenko, I. V. Hicks, S. Sachdeva
Posted online, January 2006
"Network Analysis of Knowledge Construction in Asynchronous Learning Networks"
by Aviv, Reuven; Erlich, Zippy; Ravid, Gilad; Geva, Aviva
in the Journal of Asynchronous Learning Networks, Vol 7, No 3, 2003
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
Keywords
data mining; graph theory; terrorism; covert networks; investigative data mining; social network analysis; structural analysis; structural cohesion; terrorist network destabilization; Application software; Computer science; Data engineering; Data mining; Educational institutions; Graph theory; Mathematical model; Robustness; Social network services; Terrorism;
fLanguage
English
Publisher
ieee
Conference_Titel
Availability, Reliability and Security, 2007. ARES 2007. The Second International Conference on
Conference_Location
Vienna
Print_ISBN
0-7695-2775-2
Type
conf
DOI
10.1109/ARES.2007.70
Filename
4159885
Link To Document