A Survey on Terrorist Network Mining: Current Trends and Opportunities

Along with the modernization and widespread usage of Internet, the security of the mankind has become one of the major issues today. The threat of human society from the terrorists is the challenge faced dominantly. Advancement in the technology has not only helped the common people for the growth but also these inhuman people to adversely affect the society with sophisticated techniques. In this regard, the law-enforcement agencies are aiming to prevent future attacks. To do so, the terrorist networks are being analyzed and detected. To achieve this, the law enforcement agencies are using data mining techniques as one of the effective solution. One such technique of data mining is Social network analysis which studies terrorist networks for the identification of relationships and associations that may exist between terrorist nodes. Terrorist activities can also be detected by means of analyzing Web traffic content. This paper studies social network analysis, web traffic content and explores various ways for identifying terrorist activities.

[1]  Rayford B. Vaughn,et al.  An improved algorithm for fuzzy data mining for intrusion detection , 2002, 2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622).

[2]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[3]  Jian Pei,et al.  Data Mining: Concepts and Techniques, 3rd edition , 2006 .

[4]  M. J. Hosseinpour,et al.  Notice of Violation of IEEE Publication Principles Detecting Terror-Related Activities on the Web with Using Data Mining Techniques , 2009 .

[5]  Philip Vos Fellman,et al.  Modeling Terrorist Networks, Complex Systems at the Mid-range , 2014, ArXiv.

[6]  Jiawei Han,et al.  Data Mining: Concepts and Techniques, Second Edition , 2006, The Morgan Kaufmann series in data management systems.

[7]  Shingo Mabu,et al.  An Intrusion-Detection Model Based on Fuzzy Class-Association-Rule Mining Using Genetic Network Programming , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[8]  Nasrullah Memon,et al.  Notice of Violation of IEEE Publication PrinciplesPractical approaches for analysis, visualization and destabilizing terrorist networks , 2006, First International Conference on Availability, Reliability and Security (ARES'06).

[9]  Daniel T. Larose,et al.  Discovering Knowledge in Data: An Introduction to Data Mining , 2005 .

[10]  A. K. Pujari,et al.  Data Mining Techniques , 2006 .

[11]  Wang Jiaxin,et al.  Investigative Data Mining: Identifying Key Nodes in Terrorist Networks , 2006, 2006 IEEE International Multitopic Conference.

[12]  R.K. Cunningham,et al.  Evaluating intrusion detection systems: the 1998 DARPA off-line intrusion detection evaluation , 2000, Proceedings DARPA Information Survivability Conference and Exposition. DISCEX'00.

[13]  Limsoon Wong,et al.  DATA MINING TECHNIQUES , 2003 .