Notice of Violation of IEEE Publication Principles - Novel Algorithms for Subgroup Detection in Terrorist Networks

Abstract

Notice of Violation of IEEE Publication Principles<br><br> "Novel Algorithms for Subgroup Detection in Terrorist Networks"<br> by Nasrullah Memon, Abdul Rasool Qureshi, Uffe Kock Wiil, and David L. Hicks<br> in the Proceedings of the 2009 International Conference on Availability, Reliability and Security, March 2009, pp. 572-577<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 contains significant portions of original text from the papers cited below. The original text was copied with insufficient attribution (including appropriate references to the original author(s) and/or paper titles) and without permission. The lead author, Nasrullah Memon, was found to be solely responsible for the violation.<br><br> Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following articles:<br><br> "Balancing Systematic and Flexible Exploration of Social Networks"<br> by Adam Perer, Ben Shneiderman<br> in the IEEE Transactions on Visualization and Computer Graphics, Vol. 12, No. 5<br> Sept/Oct 2006, pp. 693-700<br> "Mining for Offender Group Detection and Story of a Police Operation"<br> by Fatih Ozgul, Julian Bondy, Hakan Aksoy<br> in the Proceedings of the Sixth Australasian Data Mining Conference (AusDM 2007), Gold Coast, Australia. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 70, December 2007, pp. 185-189<br><br> "The Exploratory Construction of Database Views"<br> by M.N. Smith, P.J.H. King<br> in Research Report BBKCS-02-02, School of Computer Science and Information Systems, Birbeck College, University of London. 2002. http://www.dcs.bbk.ac.uk/TriStarp/pubs/ECoDV2002.pdf<br><br> <br/> 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.