Bayesian multivariate models for case assessment in dynamic signature cases. (January 2021) - Linden, Jacques; Taroni, Franco; Marquis, Raymond; Bozza, Silvia
Highlights: Description of the methodological and technical framework for the analysis of dynamic signatures. Description of a probabilistic framework for the assessment of dynamic signature evidence. Assessment of model performances for signature evidence. Abstract: Dynamic signatures are recordings of signatures made on digitizing devices such as tablet PCs. These handwritten signatures contain both dynamic and spatial information on every data point collected during the signature movement and can therefore be described in the form of multivariate data. The management of dynamic signatures represents a challenge for the forensic science community through its novelty and the volume of data available. Much as for static signatures, the authenticity of dynamic signatures may be doubted, which leads to a forensic examination of the unknown source signature. The Bayes' factor, as measure of evidential support, can be assigned with statistical models to discriminate between competing propositions. In this respect, the limitations of existing probabilistic solutions to deal with dynamic signature evidence is pointed out and explained in detail. In particular, the necessity to remove the independence assumption between questioned and reference material is emphasized.