A Survey on Analysis Terrorist Networks with Complex Networks

نوع المستند : المقالة الأصلية

المؤلف

المستخلص

 Many researchers, after the terrorist attacks in 2001, have been looked for understand the functions and structures of terrorist networks. This paper analyzes various techniques and methods proposed in this area and discuss how the complex network helps us to identify the important nodes in the terrorism network. By use the standard social network analysis (SNA) measures such as (degree, betweenness, closeness) centrality, and apply techniques from different field such as game theory, Fuzzy Analytic Network method. Furthermore, a little of research are focus on the how we can predict the terrorist threat, which is hard for uncertain or hidden information. After analyzing the techniques and show the challenges in the terrorist network a proposal solution is made in conclusion Index Terms— Terrorist Network, Centrality measures, covered group,
Social network analysis (SNA)

References
1) Worldwi NCTC, Statista 2015 Available :
http://www.statista.com/statistics/202871/number-of-fatalities-by-terrorist-attacks-worldwide/
2) U. K. Wiil, N. Memon, and P. Karampelas, “Detecting New Trends in Terrorist Networks," in Advances in Social Networks Analysis and Mining (ASONAM), 2010 International Conference on, pp.435-440.
3) Valdis E. Krebs, Uncloaking Terrorist Networks (URL:http://www.firstmonday.dk/issues/issue74/kreb) First Monday, volume 7, number 4, 2002
4) Mukherjee, M., & Holder, L. B. Graph-based data mining on social networks (Doctoral dissertation, University of Texas at Arlington), 2004
5) Freeman, L. C.: Centrality in Social Networks: Conceptual Clarification. Social Networks 1 (1979) 215-240
6) D. Chen, L. Lü, M.-S. Shang, Y.-C. Zhang, and T. Zhou, "Identifying influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, vol. 391, pp. 1777-1787, 2012.
7) Kas, M.; Wachs, M.; Carley, K.M.; Carley, L.R., "Incremental algorithm for updating betweenness centrality in dynamically growing networks," Advances in Social Networks Analysis and Mining , 2013 IEEE/ACM International Conference on , vol., no., pp.33,40, 25-28 Aug. 2013
8) M. Kas, K. M. Carley, and L.R. Carley, "Incremental Closeness Centrality for Dynamically Changing Social Networks," in Workshop on the Semantic and Dynamic Analysis of Information Networks, 2013.
9) Page, L., Brin, S., Motwani, R., & Winograd, T. “The PageRank citation ranking: Bringing order to the web”. Stanford Digital Library Project. 1999
10) Crucitti, P., Latora, V., Marchiori, M., Ebeling, W. & Spagnolo, B. LOCATING CRITICAL LINES IN HIGH-VOLTAGE ELECTRICAL POWER GRIDS. Fluctuation & Noise Letters, 5(2), L201-L208.2005
11) Vito Latora, Massimo Marchiori,” How the science of complex networks can help developing strategies against terrorism”, Chaos, Solitons & Fractals, Volume 20, Issue 1, Pages 69-75, April 2004.
12) Li Ze; Sun Duo-yong; Guo Shu-quan; Li Bo, "Detecting key individuals in terrorist network based on FANP model," Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on, pp.724,727, 17-20 Aug. 2014
13) Wiil, U.K.; Memon, N.; Karampelas, P., "Detecting New Trends in Terrorist Networks," Advances in Social Networks Analysis and Mining (ASONAM), 2010 International Conference on, pp.435,440, 9-11Aug. 2010
14) An article published in The Times Of India. Available online at http://timesofindia.indiatimes.com/india/ Pak- Army- officer- linked- to- Rana-Headley/articleshow/5249930.cms accessed on January 10, 2010.
15) Michalak, T.P.; Rahwan, T.; Skibski, O.; Wooldridge, M., "Defeating Terrorist Networks with Game Theory," Intelligent Systems, IEEE , vol.30, no.1, pp.53,61, Jan.-Feb. 2015