{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T16:21:39Z","timestamp":1778343699300,"version":"3.51.4"},"reference-count":42,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,1,6]],"date-time":"2021-01-06T00:00:00Z","timestamp":1609891200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"\u00abLeading research center (LRC) \u00abTrusted Sensor Systems\u00bb, financial support provided by Ministry of Digital Development, Communications and Mass Media of the Russian Federation and Russian Venture Company (RVC JSC)","award":["Agreement \u2116009\/20 dated 04\/10\/2020)"],"award-info":[{"award-number":["Agreement \u2116009\/20 dated 04\/10\/2020)"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>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\u2019s 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.<\/jats:p>","DOI":"10.3390\/info12010019","type":"journal-article","created":{"date-parts":[[2021,1,6]],"date-time":"2021-01-06T09:15:16Z","timestamp":1609924516000},"page":"19","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Generation of an EDS Key Based on a Graphic Image of a Subject\u2019s Face Using the RC4 Algorithm"],"prefix":"10.3390","volume":"12","author":[{"given":"Alexey","family":"Semenkov","sequence":"first","affiliation":[{"name":"Faculty of Security, Tomsk State University of Control Systems and Radioelectronics, 40 Lenina Prospect, 634050 Tomsk, Russia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0875-3301","authenticated-orcid":false,"given":"Dmitry","family":"Bragin","sequence":"additional","affiliation":[{"name":"Faculty of Security, Tomsk State University of Control Systems and Radioelectronics, 40 Lenina Prospect, 634050 Tomsk, Russia"}]},{"given":"Yakov","family":"Usoltsev","sequence":"additional","affiliation":[{"name":"Faculty of Security, Tomsk State University of Control Systems and Radioelectronics, 40 Lenina Prospect, 634050 Tomsk, Russia"}]},{"given":"Anton","family":"Konev","sequence":"additional","affiliation":[{"name":"Faculty of Security, Tomsk State University of Control Systems and Radioelectronics, 40 Lenina Prospect, 634050 Tomsk, Russia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3222-9956","authenticated-orcid":false,"given":"Evgeny","family":"Kostuchenko","sequence":"additional","affiliation":[{"name":"Faculty of Security, Tomsk State University of Control Systems and Radioelectronics, 40 Lenina Prospect, 634050 Tomsk, Russia"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1019","DOI":"10.1016\/S0893-6080(05)80157-1","article-title":"A Fast Dynamic Link Matching Algorithm for Invariant Pattern Recognition","volume":"7","author":"Konen","year":"1994","journal-title":"Neural Netw."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"101038","DOI":"10.1016\/j.ecoinf.2019.101038","article-title":"RoI Detection and Segmentation Algorithms for Marine Mammals Photo-Identification","volume":"56","author":"Pollicelli","year":"2020","journal-title":"Ecol. 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