Steganalysis of LSB matching using differences between nonadjacent pixels

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• 作者：Zhihua Xia ; Xinhui Wang ; Xingming Sun ; Quansheng Liu…
• 关键词：Steganalysis ; LSB matching ; Difference histogram ; Characteristic function ; Support vector machine
• 刊名：Multimedia Tools and Applications
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：75
• 期：4
• 页码：1947-1962
• 全文大小：1,191 KB
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• 作者单位：Zhihua Xia (1) (2)
  Xinhui Wang (1) (2)
  Xingming Sun (1) (2)
  Quansheng Liu (3)
  Naixue Xiong (4)
  
  1. Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology, Nanjing, 210044, China
  2. School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing, 210044, China
  3. UMR6205, LMBA, Campus de Tohannic, Université de Bretagne-Sud, BP573, F-56000, Vannes, France
  4. School of Computer Science, Colorado Technical University, Colorado Spring, CO, 80907, USA
  
• 刊物类别：Computer Science
• 刊物主题：Multimedia Information Systems
  Computer Communication Networks
  Data Structures, Cryptology and Information Theory
  Special Purpose and Application-Based Systems
  
• 出版者：Springer Netherlands
• ISSN：1573-7721

文摘

This paper models the messages embedded by spatial least significant bit (LSB) matching as independent noises to the cover image, and reveals that the histogram of the differences between pixel gray values is smoothed by the stego bits despite a large distance between the pixels. Using the characteristic function of difference histogram (DHCF), we prove that the center of mass of DHCF (DHCF COM) decreases after messages are embedded. Accordingly, the DHCF COMs are calculated as distinguishing features from the pixel pairs with different distances. The features are calibrated with an image generated by average operation, and then used to train a support vector machine (SVM) classifier. The experimental results prove that the features extracted from the differences between nonadjacent pixels can help to tackle LSB matching as well.