On the issue of ensuring secure access to information systems using biometric authentication based on a fuzzy image of the user’s identity and neural network transformations

Objective. In modern conditions, cryptographic personal authentication technologies are used to access information systems, based on processing biometric information and converting the user’s biometric images into his personal access code. A current area of research is the use of neural network technologies in organizing secure access to information systems. Biometric authentication tools can be classified as highly reliable only if they include cryptographic authentication mechanisms that work together with biometric authentication mechanisms through the conversion of biometric images into a unique cryptographic access code; in this case, a set of biometric identifiers of the user’s identity form his fuzzy image, which is used later during authentication. The purpose of the study is to develop an algorithm for providing secure access to information systems using biometric authentication based on a fuzzy image of the user’s identity and neural network transformations. Method. The development of the algorithm is based on the use of fuzzy logic methods and neural networks. Result. The work reveals the features of biometric identification of the user of information systems. An algorithm is proposed for providing secure access to information systems using biometric authentication based on a fuzzy image of the user’s personality and neural network transformations. Conclusions. Based on two-step authentication of the user’s identity, secure access to the information systems of registered users is implemented. A listing of the program code in Python for creating and training a neural network of a bioidentifier classifier is provided. The materials of the article are of practical value for specialists in the field of providing secure access to information systems using artificial intelligence.