Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/317571
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dc.coverage.spatial
dc.date.accessioned2021-03-09T12:18:24Z-
dc.date.available2021-03-09T12:18:24Z-
dc.identifier.urihttp://hdl.handle.net/10603/317571-
dc.description.abstractCovert transmission of information hidden in different media to either a general newlineor targeted audience constitutes steganography. However, this technique can be newlinemisused to transmit undesirable information. Traditionally the removal of such newlinecontent necessitated the knowledge of the steganographic algorithm used. However, newlinewe address the scenario where such stego is removed using generic image newlineprocessing operations which involves convolution and smoothening of image depending newlineon the type of filter and the window size used. The degradation caused newlineby these operations are partially restored using variational deconvolution. This removal newlineprocess can be done without assuming any knowledge of the steganographic newlinealgorithm used. Our procedure has been tested on a variety of steganographic newlinealgorithms including Random LSB, _ LSB, PVD, OutGuess, HUGO-BD, WOW, newlineSynch and J-UNIWARD. By applying universal steganalysis we found that all images newlinewhich have been subjected to our procedure have become stego free. However, newlinea direct evaluation of the stego content assuming knowledge of the stego content newlineand its location showed that 80 percentage of the stego is removed without significantly impacting the visual image quality. Video stream containing isolated newlinestatic images have been addressed in this thesis. The peak signal-to-noise ratio newlineand structural similarity metric values of cleaned images and videos are found to newlinebe in the range 30 dB - 40 dB and 0.81 - 0.99 respectively newline newline
dc.format.extentx,142
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleGeneralised image quality preserving algorithm for stego destruction
dc.title.alternative
dc.creator.researcherAmritha PP
dc.subject.keywordEngineering and Technology, Radiometric and geometric operations, steganalysis, steganography; Computation theory, Image processing, Intelligent computing, Markov feature,PSNR, SSIM-Structured Similarity Index Measure
dc.description.note
dc.contributor.guideSethumadhavan M
dc.publisher.placeCoimbatore
dc.publisher.universityAmrita Vishwa Vidyapeetham (University)
dc.publisher.institutionCenter for Cyber Security Systems and Networks
dc.date.registered2009
dc.date.completed2019
dc.date.awarded2019
dc.format.dimensions
dc.format.accompanyingmaterialCD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Center for Cyber Security Systems and Networks

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01_title.pdfAttached File116.37 kBAdobe PDFView/Open
02_certificate.pdf142.14 kBAdobe PDFView/Open
03_declaration.pdf103.29 kBAdobe PDFView/Open
04_contents.pdf115.74 kBAdobe PDFView/Open
05_acknowledgement.pdf65.57 kBAdobe PDFView/Open
06_list of tables.pdf51.84 kBAdobe PDFView/Open
07_list of figure.pdf102.81 kBAdobe PDFView/Open
08_abbreviation.pdf107.74 kBAdobe PDFView/Open
09_list of symbols.pdf124.5 kBAdobe PDFView/Open
10_abstract.pdf62.09 kBAdobe PDFView/Open
11_chapter 1.pdf121.92 kBAdobe PDFView/Open
12_chapter 2.pdf365.18 kBAdobe PDFView/Open
13_chapter 3.pdf567.89 kBAdobe PDFView/Open
14_chapter 4.pdf120.94 kBAdobe PDFView/Open
15_chapter 5.pdf446.7 kBAdobe PDFView/Open
16_chapter 6.pdf1.02 MBAdobe PDFView/Open
17_chapter 7.pdf259.31 kBAdobe PDFView/Open
18_chapter 8.pdf481.87 kBAdobe PDFView/Open
19_chapter 9.pdf74.87 kBAdobe PDFView/Open
20_references.pdf118.15 kBAdobe PDFView/Open
21_publications.pdf81.12 kBAdobe PDFView/Open
80_recommendation.pdf195.26 kBAdobe PDFView/Open


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