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A Framework for the Adoption of Biometric ATM Authentication in the Kenyan Banks

Date:2021-09-16

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Author:fraud transaction monitoring    kyc identity

Keywords:kyc manual,    mobile id verification,    negative news screening,    pep person meaning,    pep in finance,  '+video +KYC

Description:

Face Liveness Detection Based on Perceptual Image Quality Assessment Features with Multi-scale Analysis
Facebook use was related to more negative social comparison.?More negative social comparison was related to more negative self-perception.?Facebook use was indirectly related to more negative self-perception.?Happiness moderated the relationship between Facebook use and social comparison.?Facebook use was more strongly related to negative outcomes for unhappier people.
The primary objective of this paper is to propose a complete methodology for eye liveness detection based on pupil dynamics. This method may serve as a component of presentation attack detection in iris recognition systems, making them more secure. Due to a lack of public databases that would support this research, we have built our own iris capture device to register pupil size changes under visible light stimuli, and registered 204 observations for 26 subjects (52 different irides), each containing 750 iris images taken every 40 ms. Each measurement registers the spontaneous pupil oscillations and its reaction after a sudden increase of the intensity of visible light. The Kohn and Clynes pupil dynamics model is used to describe these changes; hence we convert each observation into a feature space defined by model parameters. To answer the question whether the eye is alive (that is, if it reacts to light changes as a human eye) or the presentation is suspicious (that is, if it reacts oddly or no reaction is observed), we use linear and non-linear Support Vector Machines to classify natural reaction and spontaneous oscillations, simultaneously investigating the goodness of fit to reject bad modeling. Our experiments show that this approach can achieve a perfect performance for the data we have collected: all normal reactions are correctly differentiated from spontaneous oscillations. We investigated the shortest observation time required to model the pupil reaction, and found that time periods not exceeding 3 seconds are adequate to offer a perfect performance.

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