The CriLiM Methodology: Crime Linkage with a Fuzzy MCDM Approach

Author

Albertetti, Fabrizio ; Cotofrei, Paul ; Grossrieder, Lionel ; Ribaux, Olivier ; Stoffel, Kilian

Author_Institution

Inf. Manage. Inst., Univ. of Neuchatel, Neuchatel, Switzerland

fYear

2013

fDate

12-14 Aug. 2013

Firstpage

67

Lastpage

74

Abstract

Grouping events having similarities has always been interesting for analysts. Actually, when a label is put on top of a set of events to denote they share common properties, the automation and the capability to conduct reasoning with this set drastically increase. This is particularly true when considering criminal events for crime analysts, conjunction, interpretation and explanation can be key success factors to apprehend criminals. In this paper, we present the CriLiM methodology for investigating both serious and high-volume crime. Our artifact consists in implementing a tailored computerized crime linkage system, based on a fuzzy MCDM approach in order to combine spatio-temporal, behavioral, and forensic information. As a proof of concept, series in burglaries are examined from real data and compared to expert results.

Keywords

criminal law; decision making; digital forensics; fuzzy set theory; police data processing; spatiotemporal phenomena; CriLiM methodology; behavioral information; crime analysts; criminal events; forensic information; fuzzy MCDM approach; grouping events; high-volume crime; multicriteria decision making; reasoning; serious crime; spatio-temporal information; tailored computerized crime linkage system; Cognition; Context; Couplings; Decision making; Forensics; Fuzzy sets; Crime analysis; crime linkage; fuzzy MCDM;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligence and Security Informatics Conference (EISIC), 2013 European

Conference_Location

Uppsala

Type

conf

DOI

10.1109/EISIC.2013.17

Filename

6657127