{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T04:25:46Z","timestamp":1775190346245,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T00:00:00Z","timestamp":1656288000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>This paper puts forward a new algorithm that utilizes compressed sensing and two chaotic systems to complete image compression and encryption concurrently. First, the hash function was utilized to obtain the initial parameters of two chaotic maps, which were the 2D-SLIM and 2D-SCLMS maps, respectively. Second, a sparse coefficient matrix was transformed from the plain image through discrete wavelet transform. In addition, one of the chaotic sequences created by 2D-SCLMS system performed pixel transformation on the sparse coefficient matrix. The other chaotic sequences created by 2D-SLIM were utilized to generate a measurement matrix and perform compressed sensing operations. Subsequently, the matrix rotation was combined with row scrambling and column scrambling, respectively. Finally, the bit-cycle operation and the matrix double XOR were implemented to acquire the ciphertext image. Simulation experiment analysis showed that the compressed encryption scheme has advantages in compression performance, key space, and sensitivity, and is resistant to statistical attacks, violent attacks, and noise attacks.<\/jats:p>","DOI":"10.3390\/e24070885","type":"journal-article","created":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T22:31:14Z","timestamp":1656369074000},"page":"885","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Efficient Entropic Security with Joint Compression and Encryption Approach Based on Compressed Sensing with Multiple Chaotic Systems"],"prefix":"10.3390","volume":"24","author":[{"given":"Jingya","family":"Wang","sequence":"first","affiliation":[{"name":"School of Science, Harbin University of Science and Technology, Harbin 150080, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0111-8559","authenticated-orcid":false,"given":"Xianhua","family":"Song","sequence":"additional","affiliation":[{"name":"School of Science, Harbin University of Science and Technology, Harbin 150080, China"}]},{"given":"Ahmed A. Abd","family":"El-Latif","sequence":"additional","affiliation":[{"name":"EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia"},{"name":"Department of Mathematics and Computer Science, Faculty of Science, Menoufia University, Shebin El-Koom 32511, Egypt"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"526","DOI":"10.1016\/j.protcy.2012.10.063","article-title":"Block encoding of color histogram for content based image retrieval applications","volume":"6","author":"Shaila","year":"2012","journal-title":"Procedia Technol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.jvcir.2016.01.003","article-title":"Indexing and encoding based image feature representation with bin overlapped similarity measure for CBIR applications","volume":"36","author":"Shaila","year":"2016","journal-title":"J. Vis. 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