{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T04:33:53Z","timestamp":1762058033628,"version":"build-2065373602"},"reference-count":75,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T00:00:00Z","timestamp":1656892800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"MEXT Quantum Leap Flagship Program","award":["JPMXS0118067285","JPMXS0120319794","19K22849","21H04879"],"award-info":[{"award-number":["JPMXS0118067285","JPMXS0120319794","19K22849","21H04879"]}]},{"name":"JSPS KAKENHI","award":["JPMXS0118067285","JPMXS0120319794","19K22849","21H04879"],"award-info":[{"award-number":["JPMXS0118067285","JPMXS0120319794","19K22849","21H04879"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Many security-related scenarios including cryptography depend on the random generation of passwords, permutations, Latin squares, CAPTCHAs and other types of non-numerical entities. Random generation of each entity type is a different problem with different solutions. This study is an attempt at a unified solution for all of the mentioned problems. This paper is the first of its kind to pose, formulate, analyze and solve the problem of random object generation as the general problem of generating random non-numerical entities. We examine solving the problem via connecting it to the well-studied random number generation problem. To this end, we highlight the challenges and propose solutions for each of them. We explain our method using a case study; random Latin square generation.<\/jats:p>","DOI":"10.3390\/e24070928","type":"journal-article","created":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T11:15:05Z","timestamp":1656933305000},"page":"928","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["From Random Numbers to Random Objects"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6691-0988","authenticated-orcid":false,"given":"Behrouz","family":"Zolfaghari","sequence":"first","affiliation":[{"name":"Cyber Science Lab, School of Computer Science, University of Guelph, Guelph, ON N1G 2W1, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3301-0232","authenticated-orcid":false,"given":"Khodakhast","family":"Bibak","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, Miami University, Oxford, OH 45056, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8994-729X","authenticated-orcid":false,"given":"Takeshi","family":"Koshiba","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Faculty of Education and Integrated Arts and Sciences, Waseda University, Tokyo 169-8050, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1109\/TDSC.2020.2987025","article-title":"Deepmnemonic: Password mnemonic generation via deep attentive encoder-decoder model","volume":"19","author":"Cheng","year":"2022","journal-title":"IEEE Trans. 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