Attacks on Steganographic Systems
IH '99 Proceedings of the Third International Workshop on Information Hiding
IHW '01 Proceedings of the 4th International Workshop on Information Hiding
Detection of LSB Steganography via Sample Pair Analysis
IH '02 Revised Papers from the 5th International Workshop on Information Hiding
A steganographic method for images by pixel-value differencing
Pattern Recognition Letters
Detecting LSB Steganography Based on Dynamic Masks
ISDA '05 Proceedings of the 5th International Conference on Intelligent Systems Design and Applications
Reliable detection of LSB steganography in color and grayscale images
MM&Sec '01 Proceedings of the 2001 workshop on Multimedia and security: new challenges
Defending against statistical steganalysis
SSYM'01 Proceedings of the 10th conference on USENIX Security Symposium - Volume 10
An improved sample pairs method for detection of LSB embedding
IH'04 Proceedings of the 6th international conference on Information Hiding
Steganalysis of Multi Bit Plane Image Steganography
IWDW '07 Proceedings of the 6th International Workshop on Digital Watermarking
Edge adaptive image steganography based on LSB matching revisited
IEEE Transactions on Information Forensics and Security
Tradeoff between energy savings and privacy protection in computation offloading
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
A more secure steganography based on adaptive pixel-value differencing scheme
Multimedia Tools and Applications
Steganalysis of adaptive image steganography in multiple gray code bit-planes
Multimedia Tools and Applications
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This paper addresses a novel steganography method for images. Most statistical steganalysis algorithms are strong to defeat previous steganography algorithms. RS steganalysis and pixel difference histogram analysis are two well-known statistical steganalysis algorithms which detect non-random changes caused by embedding a secret message into cover image. In this paper, we first explain how two steganalysis algorithms exploit the effect of the non-random changes and then propose a new steganography method that avoids the non-random changes to evade statistical analysis methods. For this purpose, we adjust the embedding process to be more adaptive to cover image by considering embedding in Gray code bit planes, not natural binary bit planes, of cover images, and two parameters: (1) similarity threshold for selecting non-flat area in lower bit planes, and (2) size of flat blocks n×n in embedding bit planes. Experimental results show that the secret messages embedded by our method are undetectable under RS steganalysis and pixel difference histogram analysis.