ANR IDFraud – An Operational Automatic Framework for Identity Document Fraud Detection and Profiling

The first contribution of IDFRAud project consists in proposing an automatic solution for ID analysis and integrity verification. Our ID analysis goes through three processes: classification, text extraction and ID verification. The three processes rely on a set of rules that are externalized in formal manner in order to allow easy management and evolving capabilities. This leads us to the second contribution of IDFRAud: an ID knowledge management module. The third objective of IDFRAud project is to address the forensic link detection problem and to propose an automatic analysis engine that can be continuously applied on the detected fraud ID database. Cluster analysis methods are used to discover relations between false IDs in their multidimensional feature space. This pattern extraction module will be coupled with a suitable visualization mechanism in order to facilitate the comprehension and the analysis of extracted groups of inter-linked fraud cases.

Dates: February 2015 – January 2018
Contact: Teddy Furon


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