Generation of an EDS Key Based on a Graphic Image of a Subject’s Face Using the RC4 Algorithm

Modern facial recognition algorithms make it possible to identify system users by their appearance with a high level of accuracy. In such cases, an image of the user’s face is converted to parameters that later are used in a recognition process. On the other hand, the obtained parameters can be used...

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Main Authors: Alexey Semenkov, Dmitry Bragin, Yakov Usoltsev, Anton Konev, Evgeny Kostuchenko
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Information
Subjects:
Online Access:https://www.mdpi.com/2078-2489/12/1/19
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spelling doaj-91205c783d6b4e4b965f21c081f6550b2021-01-07T00:02:13ZengMDPI AGInformation2078-24892021-01-0112191910.3390/info12010019Generation of an EDS Key Based on a Graphic Image of a Subject’s Face Using the RC4 AlgorithmAlexey Semenkov0Dmitry Bragin1Yakov Usoltsev2Anton Konev3Evgeny Kostuchenko4Faculty of Security, Tomsk State University of Control Systems and Radioelectronics, 40 Lenina Prospect, 634050 Tomsk, RussiaFaculty of Security, Tomsk State University of Control Systems and Radioelectronics, 40 Lenina Prospect, 634050 Tomsk, RussiaFaculty of Security, Tomsk State University of Control Systems and Radioelectronics, 40 Lenina Prospect, 634050 Tomsk, RussiaFaculty of Security, Tomsk State University of Control Systems and Radioelectronics, 40 Lenina Prospect, 634050 Tomsk, RussiaFaculty of Security, Tomsk State University of Control Systems and Radioelectronics, 40 Lenina Prospect, 634050 Tomsk, RussiaModern facial recognition algorithms make it possible to identify system users by their appearance with a high level of accuracy. In such cases, an image of the user’s face is converted to parameters that later are used in a recognition process. On the other hand, the obtained parameters can be used as data for pseudo-random number generators. However, the closeness of the sequence generated by such a generator to a truly random one is questionable. This paper proposes a system which is able to authenticate users by their face, and generate pseudo-random values based on the facial image that will later serve to generate an encryption key. The generator of a random value was tested with the NIST Statistical Test Suite. The subsystem of image recognition was also tested under various conditions of taking the image. The test results of the random value generator show a satisfactory level of randomness, i.e., an average of 0.47 random generation (NIST test), with 95% accuracy of the system as a whole.https://www.mdpi.com/2078-2489/12/1/19digital signaturecomputer visioncryptographysecurityauthenticityalgorithms
collection DOAJ
language English
format Article
sources DOAJ
author Alexey Semenkov
Dmitry Bragin
Yakov Usoltsev
Anton Konev
Evgeny Kostuchenko
spellingShingle Alexey Semenkov
Dmitry Bragin
Yakov Usoltsev
Anton Konev
Evgeny Kostuchenko
Generation of an EDS Key Based on a Graphic Image of a Subject’s Face Using the RC4 Algorithm
Information
digital signature
computer vision
cryptography
security
authenticity
algorithms
author_facet Alexey Semenkov
Dmitry Bragin
Yakov Usoltsev
Anton Konev
Evgeny Kostuchenko
author_sort Alexey Semenkov
title Generation of an EDS Key Based on a Graphic Image of a Subject’s Face Using the RC4 Algorithm
title_short Generation of an EDS Key Based on a Graphic Image of a Subject’s Face Using the RC4 Algorithm
title_full Generation of an EDS Key Based on a Graphic Image of a Subject’s Face Using the RC4 Algorithm
title_fullStr Generation of an EDS Key Based on a Graphic Image of a Subject’s Face Using the RC4 Algorithm
title_full_unstemmed Generation of an EDS Key Based on a Graphic Image of a Subject’s Face Using the RC4 Algorithm
title_sort generation of an eds key based on a graphic image of a subject’s face using the rc4 algorithm
publisher MDPI AG
series Information
issn 2078-2489
publishDate 2021-01-01
description Modern facial recognition algorithms make it possible to identify system users by their appearance with a high level of accuracy. In such cases, an image of the user’s face is converted to parameters that later are used in a recognition process. On the other hand, the obtained parameters can be used as data for pseudo-random number generators. However, the closeness of the sequence generated by such a generator to a truly random one is questionable. This paper proposes a system which is able to authenticate users by their face, and generate pseudo-random values based on the facial image that will later serve to generate an encryption key. The generator of a random value was tested with the NIST Statistical Test Suite. The subsystem of image recognition was also tested under various conditions of taking the image. The test results of the random value generator show a satisfactory level of randomness, i.e., an average of 0.47 random generation (NIST test), with 95% accuracy of the system as a whole.
topic digital signature
computer vision
cryptography
security
authenticity
algorithms
url https://www.mdpi.com/2078-2489/12/1/19
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