{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T20:05:47Z","timestamp":1774469147980,"version":"3.50.1"},"reference-count":33,"publisher":"Association for Computing Machinery (ACM)","issue":"2s","license":[{"start":{"date-parts":[[2023,2,17]],"date-time":"2023-02-17T00:00:00Z","timestamp":1676592000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2023,6,30]]},"abstract":"<jats:p>\n            Nowadays, the demand for digital images from different intelligent devices and sensors has dramatically increased in smart healthcare. Due to advanced low-cost and easily available tools and software, manipulation of these images is an easy task. Thus, the security of digital images is a serious challenge for the content owners, healthcare communities, and researchers against illegal access and fraudulent usage. In this article, a secure medical image encryption algorithm,\n            <jats:italic>EiMOL<\/jats:italic>\n            , based on optimization and the Lorenz system, is proposed for smart healthcare applications. In the first stage, an optimized random sequence (ORS) is generated through directed weighted complex network particle swarm optimization using the genetic algorithm (GDWCN-PSO). This random number matrix and the Lorenz system are adopted to encrypt plain medical images, obtaining the cipher messages with a relationship to the plain images. According to our obtained results, the proposed\n            <jats:italic>EiMOL<\/jats:italic>\n            encryption algorithm is effective and resistant to the many attacks on benchmark Kaggle and Open-i datasets. Further, extensive experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art approaches.\n          <\/jats:p>","DOI":"10.1145\/3561513","type":"journal-article","created":{"date-parts":[[2022,9,9]],"date-time":"2022-09-09T14:09:23Z","timestamp":1662732563000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":39,"title":["EiMOL: A Secure Medical Image Encryption Algorithm based on Optimization and the Lorenz System"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7857-5945","authenticated-orcid":false,"given":"KN","family":"Singh","sequence":"first","affiliation":[{"name":"Department of CSE, NIT Patna, Patna, Bihar, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2582-5669","authenticated-orcid":false,"given":"OP","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of CSE, NIT Patna, Patna, Bihar, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7359-2068","authenticated-orcid":false,"given":"Amit Kumar","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of CSE, NIT Patna, Patna, Bihar, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1176-1716","authenticated-orcid":false,"given":"Amrit Kumar","family":"Agrawal","sequence":"additional","affiliation":[{"name":"Galgotias College of Engineering and Technology, Greater Noida, Uttar Pradesh, India"}]}],"member":"320","published-online":{"date-parts":[[2023,2,17]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3062630"},{"issue":"2","key":"e_1_3_1_3_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3422816","article-title":"A survey on healthcare data: A security perspective","volume":"17","author":"Singh A. 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