{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T15:20:29Z","timestamp":1778599229363,"version":"3.51.4"},"reference-count":57,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2020,5,31]],"date-time":"2020-05-31T00:00:00Z","timestamp":1590883200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"University Grants Commission, INDIA","award":["21\/12\/2014(ii)EU-V, 2121440593"],"award-info":[{"award-number":["21\/12\/2014(ii)EU-V, 2121440593"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2020,5,31]]},"abstract":"<jats:p>\n            The low-cost, accessing flexibility, agility, and mobility of cloud infrastructures have attracted medical organizations to store their high-resolution data in encrypted form. Besides storage, these infrastructures provide various image processing services for plain (non-encrypted) images. Meanwhile, the privacy and security of uploaded data depend upon the reliability of the service provider(s). The enforcement of laws towards privacy policies in health-care organizations, for not disclosing their patient\u2019s sensitive and private medical information, restrict them to utilize these services. To address these privacy concerns for melanoma detection, we propose\n            <jats:italic>CryptoLesion<\/jats:italic>\n            , a privacy-preserving model for segmenting lesion region using whale optimization algorithm (WOA) over the cloud in the encrypted domain (ED). The user\u2019s image is encrypted using a permutation ordered binary number system and a random stumble matrix. The task of segmentation is accomplished by dividing an encrypted image into a pre-defined number of clusters whose optimal centroids are obtained by WOA in ED, followed by the assignment of each pixel of an encrypted image to the unique centroid. The qualitative and quantitative analysis of\n            <jats:italic>CryptoLesion<\/jats:italic>\n            is evaluated over publicly available datasets provided in\n            <jats:italic>The International Skin Imaging Collaboration<\/jats:italic>\n            Challenges in 2016, 2017, 2018, and PH\n            <jats:sup>2<\/jats:sup>\n            dataset. The segmented results obtained by\n            <jats:italic>CryptoLesion<\/jats:italic>\n            are found to be comparable with the winners of respective challenges.\n            <jats:italic>CryptoLesion<\/jats:italic>\n            is proved to be secure from a probabilistic viewpoint and various cryptographic attacks. To the best of our knowledge,\n            <jats:italic>CryptoLesion<\/jats:italic>\n            is first moving towards the direction of lesion segmentation in ED.\n          <\/jats:p>","DOI":"10.1145\/3380743","type":"journal-article","created":{"date-parts":[[2020,6,12]],"date-time":"2020-06-12T01:40:17Z","timestamp":1591926017000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["<i>CryptoLesion<\/i>"],"prefix":"10.1145","volume":"16","author":[{"given":"Vishesh Kumar","family":"Tanwar","sequence":"first","affiliation":[{"name":"Department of Mathematics, Indian Institute of Technology Roorkee, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Balasubramanian","family":"Raman","sequence":"additional","affiliation":[{"name":"Department of Computer 8 Engineering, Indian Institute of Technology Roorkee, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amitesh Singh","family":"Rajput","sequence":"additional","affiliation":[{"name":"Department of Computer 8 Engineering, Indian Institute of Technology Roorkee, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rama","family":"Bhargava","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Indian Institute of Technology Roorkee, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,6,11]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2017.2653179"},{"key":"e_1_2_2_2_1","volume-title":"Proceedings of the 18th ACM-SIAM Symposium on Discrete Algorithms. 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