Abstract
The identification of criminal networks is not a routine exploratory process within the current practice of the law enforcement authorities; rather it is triggered by specific evidence of criminal activity being investigated. A network is identified when a criminal comes to notice and any associates who could also be potentially implicated would need to be identified if only to be eliminated from the enquiries as suspects or witnesses as well as to prevent and/or detect crime. However, an identified network may not be the one causing most harm in a given area.. This paper identifies a methodology to identify all of the criminal networks that are present within a Law Enforcement Area, and, prioritises those that are causing most harm to the community. Each crime is allocated a score based on its crime type and how recently the crime was committed; the network score, which can be used as decision support to help prioritise it for law enforcement purposes, is the sum of the individual crime scores.
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References
Baker, W.E., Faulkner, R.R.: The social organization of conspiracy: Illegal networks in the heavy electrical equipment industry. American Sociological Review 58(6), 837–860 (1993)
Krebs, V.E.: Mapping Networks of Terrorist Cells. Connections 24(3), 43–52 (2001)
Sparrow, M.K.: The application of network analysis to criminal intelligence: An assessment of the prospects. Social Networks 13, 251–274 (1991)
Xu, J., Chen, H.: Criminal Network Analysis and Visualisation. CACM 48(6), 100–107 (2005)
Watts, D.J.: Networks, Dynamics and the Small World Phenomenon. American Journal of Sociology 105(2), 493–527 (1999)
Barrat, A., Weight, M.: On the properties of small world networks. Eur. Phys. J. B13, 547–560 (2000)
Uzzi, B., Spiro, J.: Collaboration and Creativity: The Small World Problem. American Journal of Sociology 111, 447–504 (2005)
Milgram, S.: The Small World. Psychology Today 2, 60–67 (1967)
Sageman, M.: Understanding Terror Networks. University of Pennsylvania Press, Philadelphia (2004)
Allanch, J., Tu, H., Singh, S., Willett, P., Pattipati, K.: Detecting, tracking and counteracting terrorist networks via hidden Markov models. In: Proceedings IEEE Aerospace Conference, pp. 2346–3257 (2004)
Xu, J., Marshall, B., Kaza, S., Chen, H.: Analyzing and Visualizing Criminal Network Dynamics: A Case Study. In: Proceedings of Intelligence and Security Informatics, pp. 232–248. Springer, Heidelberg (2004)
Klerks, P.: The Network Paradigm Applied to Criminal Organisations: Theoretical nitpicking or a relevant doctrine for investigators? Recent developments in the Netherlands. Connections 24(3), 53–65 (2001)
Wikipedia, http://en.wikipedia.org/wiki/Social_network
1nsightful Miner, http://www.insightful.com/products/iminer/default.asp
Chapman, P., Clinton, J., Kerber, R., Khbaza, T., Reinhertz, T., Sgearer, C., Wirth, R.: CRISP-DM 1.0 Step-by-step data mining guide, SPSS Inc. CRISPWP-0800, USA (2000)
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Adderley, R., Badii, A., Wu, C. (2008). The Automatic Identification and Prioritisation of Criminal Networks from Police Crime Data. In: Ortiz-Arroyo, D., Larsen, H.L., Zeng, D.D., Hicks, D., Wagner, G. (eds) Intelligence and Security Informatics. EuroIsI 2008. Lecture Notes in Computer Science, vol 5376. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89900-6_4
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DOI: https://doi.org/10.1007/978-3-540-89900-6_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89899-3
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