An image encryption scheme based on chaotic logarithmic map and key generation using deep CNN

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dc.authoridThanh, Dang/0000-0003-2025-8319
dc.authoridAKBACAK, ENVER/0000-0002-6753-7887
dc.authoridEnginoglu, Serdar/0000-0002-7188-9893
dc.authoridErkan, Ugur/0000-0002-2481-0230
dc.authoridToktas, Abdurrahim/0000-0002-7687-9061
dc.contributor.authorErkan, Ugur
dc.contributor.authorToktas, Abdurrahim
dc.contributor.authorEnginoglu, Serdar
dc.contributor.authorAkbacak, Enver
dc.contributor.authorThanh, Dang N. H.
dc.date.accessioned2025-01-27T20:12:11Z
dc.date.available2025-01-27T20:12:11Z
dc.date.issued2022
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractA secure and reliable image encryption scheme is presented, which depends on a novel chaotic log-map, deep convolution neural network (CNN) model, and bit reversion operation for the manipulation process. CNN is utilized to generate a public key to be based on the image in order to enhance the key sensitivity of the scheme. Initial values and control parameters are then obtained from the key to be used in the chaotic log-map, and thus a chaotic sequence is produced for the encrypting operations. The scheme then encrypts the images by scrambling and manipulating the pixels of images through four operations: permutation, DNA encoding, diffusion, and bit reversion. The encryption scheme is precisely examined for the well-known images in terms of various cryptanalyses such as key-space, key sensitivity, information entropy, histogram, correlation, differential attack, noisy attack, and cropping attack. To corroborate the image encryption scheme, the visual and numerical results are even compared with available scores of the state of the art. Therefore, the proposed log-map-based image encryption scheme is successfully verified and validated by superior absolute and comparative results. As future work, the proposed log-map can be extended to combinational multi-dimensional with existing efficient chaotic maps.
dc.description.sponsorshipUniversity of Economics Ho Chi Minh City, Vietnam
dc.description.sponsorshipThis research was funded by University of Economics Ho Chi Minh City, Vietnam. Fund receiver: Dr. Dang Ngoc Hoang Thanh.
dc.identifier.doi10.1007/s11042-021-11803-1
dc.identifier.endpage7391
dc.identifier.issn1380-7501
dc.identifier.issn1573-7721
dc.identifier.issue5
dc.identifier.scopus2-s2.0-85123625639
dc.identifier.scopusqualityQ1
dc.identifier.startpage7365
dc.identifier.urihttps://doi.org/10.1007/s11042-021-11803-1
dc.identifier.urihttps://hdl.handle.net/20.500.12428/20870
dc.identifier.volume81
dc.identifier.wosWOS:000748678300002
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofMultimedia Tools and Applications
dc.relation.publicationcategoryinfo:eu-repo/semantics/openAccess
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20250125
dc.subjectImage encryption
dc.subjectChaotic map
dc.subjectLogarithmic map
dc.subjectDeep convolution neural network (CNN)
dc.subjectBit reversion
dc.titleAn image encryption scheme based on chaotic logarithmic map and key generation using deep CNN
dc.typeArticle

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