ANALYSIS AND EVALUATION OF BIOMETRIC AUTHENTICATION MEANS BASED ON THE IMAGE OF THE FACE AND IRIS OF THE STAFF OF CRITICAL INFRASTRUCTURE FACILITIES

Abstract

Dedicated to the analysis and evaluation of biometric authentication systems for personnel of critical infrastructure facilities. It is shown that tools based on the image of the face and the iris of the eye have broad prospects, which is explained by the proven solutions in the field of face image analysis, the availability and distribution of video recording tools that allow the iris to be recorded simultaneously with the face with satisfactory quality. It was determined that one of the ways to improve the effectiveness of such tools is to increase the accuracy of face recognition and resistance to obstacles that cover part of the face. It is also shown that an additional direction of improving the effectiveness of biometrics can be recognition of the current psycho-emotional state of personnel of critical infrastructure facilities. The need to evaluate the effectiveness of face and emotion recognition tools based on face and iris images is determined. Based on the analysis of the literature, two groups of efficiency criteria were formed: basic and additional. Criteria characterizing the effectiveness of the recognition process are included in the main group, and criteria corresponding to the technical implementation features and service capabilities of recognition tools are included in the additional group. An evaluation of modern means of face and emotion recognition based on the image of the face and iris of the eye was carried out, and their non-compliance with a number of criteria was determined. It is proposed to correlate the ways of further research with the solution of the task of ensuring the fulfillment of the criteria related to the possibility of recognizing emotions and a person based on part of the image of the face, facial expressions and part of the image of the iris of the eye, with the technical implementation of expert solutions. The possibility of performing the specified task due to the use of modern neural network technologies is shown.