Detecting LSB Steganography in Color and Gray-Scale Images
IEEE MultiMedia
An Implementation of Key-Based Digital Signal Steganography
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 new approach to reliable detection of LSB steganography in natural images
Signal Processing - Special section: Security of data hiding technologies
Effective Steganalysis Based on Statistical Moments of Wavelet Characteristic Function
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume I - Volume 01
Image complexity and feature mining for steganalysis of least significant bit matching steganography
Information Sciences: an International Journal
Steganalysis by subtractive pixel adjacency matrix
IEEE Transactions on Information Forensics and Security
Blind statistical steganalysis of additive steganography using wavelet higher order statistics
CMS'05 Proceedings of the 9th IFIP TC-6 TC-11 international conference on Communications and Multimedia Security
Steganalysis based on differential statistics
CANS'06 Proceedings of the 5th international conference on Cryptology and Network Security
A feature-based classification technique for blind image steganalysis
IEEE Transactions on Multimedia
Steganalysis using image quality metrics
IEEE Transactions on Image Processing
Information Sciences: an International Journal
An intelligent chaotic embedding approach to enhance stego-image quality
Information Sciences: an International Journal
Information Sciences: an International Journal
IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking
A novel blind detector for additive noise steganography in JPEG decompressed images
Multimedia Tools and Applications
| Hi-index | 0.07 |
This paper presents a least significant bit (LSB) matching steganography detection method based on statistical modeling of pixel difference distributions. Previous research indicates that natural images are highly correlated in a local neighborhood and that the value zero appears most frequently in intensity differences between adjacent pixels. The statistical model of the distribution of pixel difference can be established using the Laplace distribution. LSB matching steganography randomly increases or decreases the pixel value by 1 when the message is embedded; thus, the frequency of occurrence of the value zero in pixel differences changes most dramatically during message embedding. Based on the Laplacian model of pixel difference distributions, this paper proposes a method to estimate the number of the zero difference value using the number of non-zero difference values from stego-images and uses the relative estimation error between the estimated and actual values of the number of the zero difference value as the classification feature. Experimental results indicate that the proposed algorithm is effective in detecting LSB matching steganography and can achieve better detection performance than the local extreme method under most circumstances.