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  • 标题:STEGANALYSIS ON IMAGES BASED ON THE CLASSIFICATION OF IMAGE FEATURE SETS USING SVM CLASSIFIER
  • 本地全文:下载
  • 作者:S. DEEPA ; R. UMARANI
  • 期刊名称:International Journal of Computer Science and Engineering
  • 印刷版ISSN:2278-9960
  • 电子版ISSN:2278-9979
  • 出版年度:2016
  • 卷号:5
  • 期号:5
  • 页码:15-24
  • 语种:English
  • 出版社:IASET Journals
  • 摘要:The two popular schemes used for image steganography are spatial domain embedding and transform domain embedding. Most of the steganographic techniques either use spatial domain or transform domain to embed the secret message. This work is about attack on Modern spatial domain image steganography. The previous work evaluates the performance of five state of the art content-adaptive steganographic techniques. Since WOW is believed to be a strong steganographic method which will with stand against attacks, this work, does steganalysis on WOW stego images. This paper attempts to detect the stego images created by WOW algorithm by using Chen Feature set, Subtractive Pixel Adjacency Mode (SPAM) Feature set and Ccpev Feature set. It uses a SVM based classifier to detect the stego images.
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