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  1. University of Computer Studies, Yangon
  2. Conferences

Digital Video Steganalysis Based on Statistical Features

http://hdl.handle.net/20.500.12678/0000004474
http://hdl.handle.net/20.500.12678/0000004474
67e059ab-1799-4e3f-9852-dd6358fd3e9c
ab727673-65f6-4014-96d2-7bd355736ddf
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Title
Title Digital Video Steganalysis Based on Statistical Features
Language en_US
Publication date 2012-02-28
Authors
Htet, Thu Thu
Description
Steganalysis is the art and science ofdetecting a secret communication. Hiding amessage will most likely leave detectable tracesin the cover medium. The information hidingprocess changes the statistical properties of thecover, which is a steganalyst attempts to detect.The process of attempting to detect statisticaltraces is called statistical steganalysis. Thispaper presents an improved blind steganalysistechnique to detect the presence of hiddenmessages. In order to identify and classify thetwo types of statistic texture feature are used. Thefirst type features derive from the average cooccurrence matrices. The second type features isthe grey level histogram. Support VectorMachine is considered a state-of-the-artclassification algorithm. SVM classifier isutilized as the classifier. Experimental resultsshow that this approach is very successful indetecting the information-hiding in MSU StegoVideo steganograms.
Keywords
steganalysis, histogram characteristic function, co-occurrence matrices, SVM classifier
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/2403
Journal articles
Tenth International Conference On Computer Applications (ICCA 2012)
Conference papers
Books/reports/chapters
Thesis/dissertations
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