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  • 标题:Steganalysis of YASS Using Huffman Length Statistics
  • 本地全文:下载
  • 作者:Veena H Bhat1 ; Krishna S ; P Deepa Shenoy
  • 期刊名称:International Journal of Hybrid Information Technology
  • 印刷版ISSN:1738-9968
  • 出版年度:2011
  • 卷号:4
  • 期号:3
  • 出版社:SERSC
  • 摘要:This work proposes two main contributions to statistical steganalysis of Yet Another Steganographic Scheme (YASS) in JPEG images. Firstly, this work presents a reliable blind steganalysis technique to predict YASS which is one of recent and least statistically detectable embedding scheme using only five features, four Huffman length statistics (H) and the ratio of file size to resolution (FR Index). Secondly these features are shown to be unique, accurate and monotonic over a wide range of settings for YASS and several supervised classifiers with the accuracy of prediction superior to most blind steganalyzers in vogue. Overall, the proposed model having Huffman Length Statistics as its linchpin predicts YASS with an average accuracy of over 94 percent
  • 关键词:Statistical Steganalysis; Huffman Coding; YASS.
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