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The widespread use of biometric systems entails increased interest from cybercriminals aimed at developing attacks to crack them. Thus, the development of biometric identification systems must be carried out taking into account protection against these attacks. The development of new methods and algorithms for identification based on the presentation of randomly generated key features from the biometric base of user standards will help to minimize the disadvantages of the above methods of biometric identification of users. We present an implementation of a security system based on voice identification as an access control key and a verification algorithm developed using MATLAB function blocks that can authenticate a person's identity by his or her voice. Our research has shown an accuracy of 90 % for this user identification system for individual voice characteristics. It has been experimentally proven that traditional MFCCs using DNN and i and x-vector classifiers can achieve good results. The paper considers and analyzes the most well-known approaches from the literature to the problem of user identification by voice: dynamic programming methods, vector quantization, mixtures of Gaussian processes, hidden Markov model. The developed software package for biometric identification of users by voice and the method of forming the user's voice standards implemented in the complex allows reducing the number of errors in identifying users of information systems by voice by an average of 1.5 times. Our proposed system better defines voice recognition in terms of accuracy, security and complexity. The application of the results obtained will improve the security of the identification process in information systems from various attacks.

In the area of voice recognition, many methods have been proposed over time. Automatic speaker recognition technology has reached a good level of performance, but still needs to be improved. Signature verification (SV) is one of the most common methods of identity verification in the banking sector, where for security reasons, it is very important to have an accurate method for automatic signature verification (ASV). ASV is usually solved by comparing a test signature with a registration signature(-s) signed by the person whose identity is declared in two ways: online and offline. In this study, a new ivector based method is proposed for SV online. In the proposed method, a fixed-length vector, called an i-vector, is extracted from each signature, and then this vector is used to create a template. Several methods, such as the nuisance attribute projection and the within-class covariance normalization, are also being investigated to reduce the intra-class variation in the i-vector space. At the stage of evaluation and decision-making, they also propose to apply the support vector machine with two classes. In this article, a new low-dimensional space, depending on the dynamics and the channel, is determined using a simple factor analysis, also known as i-vector. I-vectors have proven to be the most efficient functions for text independent speaker verification in recent studies.