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An efficient method to detect series of fraudulent identity documents based on digitised forensic data.

Authors :
Lugon Moulin, Solène
Weyermann, Céline
Baechler, Simon
Source :
Science & Justice; Sep2022, Vol. 62 Issue 5, p610-620, 11p
Publication Year :
2022

Abstract

• Systematic method for the profiling of fraudulent identity documents. • Visual characteristics of digitised images. • Method evaluated in real work conditions. Document fraud is a transnational form of crime, and its serial character has already been highlighted. To combat this phenomenon, the Interstate Database of Fraudulent Identity Documents (BIDIF) has been created and implemented in Switzerland. It supports the comparison of documents and the detection of series, i.e., documents that share a common source. To efficiently use such a system, forensic document examiners would benefit from a harmonised and proven profiling method. Thus, the aim of this study is to develop a method for comparing documents and establishing series. The method is meant to improve the detection capabilities of forensic document examiners operating BIDIF or engaged in the profiling of fraudulent documents. First, a method based on the visual characteristics of digitised images of fraudulent identity documents has been developed. Subsequently, the method was qualitatively and quantitatively evaluated using four tests. The first test verified the ability of the method to detect pre-existing series. The second test checked the capability of the method to detect links amongst isolated documents. Finally, two further tests were carried out to compare the method impact on the successful detection of series. These tests were carried out by professional forensic document examiners and Master students in forensic science, respectively. This allowed a comparison of the method influence on series detection. The method allowed a significant increase in the number of series and links detected, while also decreasing the occurrence of false negatives and false positives. Furthermore, links were more rapidly detected. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13550306
Volume :
62
Issue :
5
Database :
Supplemental Index
Journal :
Science & Justice
Publication Type :
Academic Journal
Accession number :
160031533
Full Text :
https://doi.org/10.1016/j.scijus.2022.09.003