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dc.contributor.authorShifa, Amna
dc.contributor.authorAfgan, Muhammad Sher
dc.contributor.authorAsghar, Mamoona Naveed
dc.contributor.authorFleury, Martin
dc.contributor.authorMemon, Imran
dc.contributor.authorAbdullah, Saima
dc.contributor.authorRasheed, Nadia
dc.date.accessioned2020-05-21T08:12:57Z
dc.date.available2020-05-21T08:12:57Z
dc.date.copyright2018
dc.date.issued2018-03-12
dc.identifier.citationShifa, A., Afgan, M.S., Asghar, M.N., Fleury, M., Memon, I., Abdullah, S., Rasheed, N. (2018). Joint crypto-stego scheme for enhanced image protection with nearest-centroid clustering. IEEE Access. 6, pp. 16189 - 16206. doi: 10.1109/ACCESS.2018.2815037en_US
dc.identifier.issn2169-3536
dc.identifier.otherArticles - Software Research Institute AITen_US
dc.identifier.urihttp://research.thea.ie/handle/20.500.12065/3223
dc.description.abstractOwing to the exceptional growth of information exchange over open communication channels within the public Internet, confidential transmission of information has become a vital current concern for organizations and individuals. In the proposed content-protection scheme, the decryption key is embedded in the encrypted image by utilizing machine learning, nearest-centroid clustering classifier, followed by Least Significant Bit matching (LSB-M) in the spatial domain. An image is first encrypted with the Advanced Encryption Standard (AES) algorithm in output feedback (OFB) mode, after which the AES key is embedded into the encrypted image. Preliminary nearest-centroid clustering followed by shuffling the sequence of pixels within the clusters before applying LSB-M makes any attack more complex, as the bits of the key are further dispersed within the encrypted image. In terms of contributions, one contribution is the direct implementation of the proposed security mechanism on color images rather than first converting them into gray tones. Another contribution of the Crypto-Stego method is that, it requires no separate key distribution mechanism to decrypt the information. In addition, a parallel-processing approach is implemented to improve the execution time and the efficiency of the scheme by exploiting system resources. Extensive experiments were performed on RGB images with different resolutions and sizes to confirm the effectiveness of the scheme. The high Structural Similarity (SSIM) index score confirmed that the overall carrier image and stego-image were unaltered by processing. While an average value over the test images of 0.0594 for Mean Squared Error (MSE) confirmed that malicious individuals cannot detect the presence of stego data in the cover image. Moreover, negligible pixel intensity histogram changes also validated the effectiveness of the proposed scheme. An average 77% efficiency and 1.5 times speed-up factor was achieved through parallel processing showed the effectiveness of the joint Crypto-Stego method for image confidentiality.en_US
dc.formatPDFen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofIEEE Accessen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/ie/*
dc.subjectCryptographyen_US
dc.subjectImage processingen_US
dc.subjectNearest-centroid clusteringen_US
dc.subjectLSB-M steganographyen_US
dc.subjectParallel processingen_US
dc.titleJoint crypto-stego scheme for enhanced image protection with nearest-centroid clustering.en_US
dc.typeArticleen_US
dc.description.peerreviewyesen_US
dc.identifier.doidoi: 10.1109/ACCESS.2018.2815037
dc.rights.accessOpen Accessen_US
dc.subject.departmentSoftware Research Institute AITen_US


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Attribution-NonCommercial-NoDerivs 3.0 Ireland
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Ireland