Complicity functions for detecting organized crime rings

Mateos Caballero, Alfonso and Jiménez Martín, Antonio and Vicente Cestero, Eloy (2016). Complicity functions for detecting organized crime rings. In: "13th International Conference on Modeling Decisions for Artificial Intelligence, (MDAI 2016)", 19-21 Sep 2016, Sant Julià de Lòria, Andorra. ISBN 978-3-319-45656-0. pp. 205-216. https://doi.org/10.1007/978-3-319-45656-0 17.

Description

Title: Complicity functions for detecting organized crime rings
Author/s:
  • Mateos Caballero, Alfonso
  • Jiménez Martín, Antonio
  • Vicente Cestero, Eloy
Item Type: Presentation at Congress or Conference (Article)
Event Title: 13th International Conference on Modeling Decisions for Artificial Intelligence, (MDAI 2016)
Event Dates: 19-21 Sep 2016
Event Location: Sant Julià de Lòria, Andorra
Title of Book: Modelling decisions for Artificial Intelligence
Date: 2016
ISBN: 978-3-319-45656-0
Volume: 9880
Subjects:
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Graph theory is an evident paradigm for analyzing social networks, which are the main tool for collective behavior research, addressing the interrelations between members of a more or less well-defined community. Particularly, social network analysis has important implications in the fight against organized crime, business associations with fraudulent purposes or terrorism. Classic centrality functions for graphs are able to identify the key players of a network or their intermediaries. However, these functions provide little information in large and heterogeneous graphs. Often the most central elements of the network (usually too many) are not related to a collective of actors of interest, such as be a group of drug traffickers or fraudsters. Instead, its high centrality is due to the good relations of these central elements with other honorable actors. In this paper we introduce complicity functions, which are capable of identifying the intermediaries in a group of actors, avoiding core elements that have nothing to do with this group. These functions can classify a group of criminals according to the strength of their relationships with other actors to facilitate the detection of organized crime rings. The proposed approach is illustrated by a real example provided by the Spanish Tax Agency, including a network of 835 companies, of which eight were fraudulent.

More information

Item ID: 46641
DC Identifier: http://oa.upm.es/46641/
OAI Identifier: oai:oa.upm.es:46641
DOI: 10.1007/978-3-319-45656-0 17
Official URL: https://link.springer.com/content/pdf/10.1007%2F978-3-319-45656-0.pdf
Deposited by: Memoria Investigacion
Deposited on: 06 Nov 2017 08:47
Last Modified: 06 Nov 2017 08:47
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