{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T11:11:07Z","timestamp":1774091467138,"version":"3.50.1"},"reference-count":52,"publisher":"Association for Computing Machinery (ACM)","issue":"3s","license":[{"start":{"date-parts":[[2023,2,25]],"date-time":"2023-02-25T00:00:00Z","timestamp":1677283200000},"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":[[2023,10,31]]},"abstract":"<jats:p>\n            With the advancement in technology, digital images can easily be transmitted and stored over the Internet. Encryption is used to avoid illegal interception of digital images. Encrypting large-sized colour images in their original dimension generally results in low encryption\/decryption speed along with exerting a burden on the limited bandwidth of the transmission channel. To address the aforementioned issues, a new encryption scheme for colour images employing convolutional autoencoder, DNA and chaos is presented in this paper. The proposed scheme has two main modules, the dimensionality conversion module using the proposed convolutional autoencoder, and the encryption\/decryption module using DNA and chaos. The dimension of the input colour image is first reduced from\n            <jats:italic>N \u00d7 M \u00d7 3<\/jats:italic>\n            to\n            <jats:italic>P \u00d7 Q<\/jats:italic>\n            gray-scale image using the encoder. Encryption and decryption are then performed in the reduced dimension space. The decrypted gray-scale image is upsampled to obtain the original colour image having dimension\n            <jats:italic>N \u00d7 M \u00d7 3<\/jats:italic>\n            . The training and validation accuracy of the proposed autoencoder is 97% and 95%, respectively. Once the autoencoder is trained, it can be used to reduce and subsequently increase the dimension of any arbitrary input colour image. The efficacy of the designed autoencoder has been demonstrated by the successful reconstruction of the compressed image into the original colour image with negligible perceptual distortion. The second major contribution presented in this paper is an image encryption scheme using DNA along with multiple chaotic sequences and substitution boxes. The security of the proposed image encryption algorithm has been gauged using several evaluation parameters, such as histogram of the cipher image, entropy, NPCR, UACI, key sensitivity, contrast, and so on. The experimental results of the proposed scheme demonstrate its effectiveness to perform colour image encryption.\n          <\/jats:p>","DOI":"10.1145\/3570165","type":"journal-article","created":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T11:33:27Z","timestamp":1667475207000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":59,"title":["A DNA Based Colour Image Encryption Scheme Using A Convolutional Autoencoder"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4796-1063","authenticated-orcid":false,"given":"Fawad","family":"Ahmed","sequence":"first","affiliation":[{"name":"Pakistan Navy Engineering College, NUST, Karachi, Sindh, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7568-9242","authenticated-orcid":false,"given":"Muneeb Ur","family":"Rehman","sequence":"additional","affiliation":[{"name":"HITEC University, Taxila, Punjab, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6289-8248","authenticated-orcid":false,"given":"Jawad","family":"Ahmad","sequence":"additional","affiliation":[{"name":"School of Computing, Edinburgh Napier University, Edinburgh, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7166-6681","authenticated-orcid":false,"given":"Muhammad Shahbaz","family":"Khan","sequence":"additional","affiliation":[{"name":"HITEC University, Taxila, Punjab, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2133-0757","authenticated-orcid":false,"given":"Wadii","family":"Boulila","sequence":"additional","affiliation":[{"name":"Prince Sultan University, Saudi Arabia and University of Manouba, Tunisia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9851-4103","authenticated-orcid":false,"given":"Gautam","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Brandon University, Canada, China Medical University, Taiwan and Lebanese American University, Chouran Beirut, Lebanon"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8768-9709","authenticated-orcid":false,"given":"Jerry Chun-Wei","family":"Lin","sequence":"additional","affiliation":[{"name":"Western Norway University of Applied Sciences, Bergen, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0809-3523","authenticated-orcid":false,"given":"William J.","family":"Buchanan","sequence":"additional","affiliation":[{"name":"School of Computing, Edinburgh Napier University, Edinburgh, United Kingdom"}]}],"member":"320","published-online":{"date-parts":[[2023,2,25]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.3390\/e22091012"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.3390\/cryptography4020018"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-015-2973-y"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/CEEC.2018.8674208"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1080\/19393555.2020.1718248"},{"key":"e_1_3_2_7_2","article-title":"End-to-end optimized image compression","author":"Ball\u00e9 Johannes","year":"2016","unstructured":"Johannes Ball\u00e9, Valero Laparra, and Eero P. 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