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dc.contributor.authorFyffe, Blair
dc.contributor.authorWang, Yunjia
dc.contributor.authorDuncan, Ishbel Mary Macdonald
dc.date.accessioned2020-07-16T14:30:02Z
dc.date.available2020-07-16T14:30:02Z
dc.date.issued2019-06-07
dc.identifier.citationFyffe , B , Wang , Y & Duncan , I M M 2019 , ' Human visual based perception of steganographic images ' , Journal of Cyber Security Technology , vol. 3 , no. 2 , pp. 61-107 . https://doi.org/10.1080/23742917.2019.1609393 , https://doi.org/10.1080/23742917.2019.1609393en
dc.identifier.issn2374-2917
dc.identifier.otherPURE: 252027723
dc.identifier.otherPURE UUID: 30f20148-ea0b-4473-944d-6735c6de132e
dc.identifier.otherRIS: urn:FF63E5BD66BE53B4F286B3E989E988D1
dc.identifier.otherRIS: urn:FF63E5BD66BE53B4F286B3E989E988D1
dc.identifier.otherORCID: /0000-0001-7297-9199/work/78891579
dc.identifier.urihttp://hdl.handle.net/10023/20273
dc.description.abstractIn 2014 it was estimated that 1.8 billion images were uploaded daily to the Internet, and in 2018 it is estimated that 3.2 billion images are shared daily. Some of these uploaded images may contain hidden information that can potentially be malicious (e.g. an image that contains hidden information regarding terrorism recruitment) or may cause serious damage (e.g. an employee wishing to hide sensitive company details in an image file and exporting the image to third parties). This research studied the most effective methods in manipulating images to hide information (Data Loss). Significant work has been done on computational algorithmic detection. Yet the desired output from this work was to find the point at which a human can no longer visually establish the difference between an original image and a manipulated image. This research examines the extent of use for file formats, bit depth alterations, least significant bits, message and audio concealment and watermark and filtering techniques for image steganography. The findings of this study indicated that audio insertion and picture insertion into cover image files are the strongest in deceiving the human eye. These results have been categorised for human visual perception in image-based steganography.
dc.format.extent48
dc.language.isoeng
dc.relation.ispartofJournal of Cyber Security Technologyen
dc.rightsCopyright © 2020 Informa UK Limited, trading as Taylor & Francis Group. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1080/23742917.2019.1609393.en
dc.subjectSteganographyen
dc.subjectData loss preventionen
dc.subjectHuman perceptionen
dc.subjectImage manipulationen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectComputer Science(all)en
dc.subjectNDASen
dc.subject.lccQA75en
dc.titleHuman visual based perception of steganographic imagesen
dc.typeJournal articleen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews.School of Computer Scienceen
dc.identifier.doihttps://doi.org/10.1080/23742917.2019.1609393
dc.description.statusPeer revieweden


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