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
A new approach to reliable detection of LSB steganography in natural images
Signal Processing - Special section: Security of data hiding technologies
Steganalysis by subtractive pixel adjacency matrix
IEEE Transactions on Information Forensics and Security
A novel visual secret sharing scheme for multiple secrets without pixel expansion
Expert Systems with Applications: An International Journal
JPEG error analysis and its applications to digital image forensics
IEEE Transactions on Information Forensics and Security
Steganalysis of LSB matching based on statistical modeling of pixel difference distributions
Information Sciences: an International Journal
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
Detection of LSB steganography via sample pair analysis
IEEE Transactions on Signal Processing
Optimized Feature Extraction for Learning-Based Image Steganalysis
IEEE Transactions on Information Forensics and Security
An Efficient Watermarking Method Based on Significant Difference of Wavelet Coefficient Quantization
IEEE Transactions on Multimedia
Spread spectrum image steganography
IEEE Transactions on Image Processing
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This paper proposes a novel universal steganalyzer for additive noise steganography in JPEG decompressed images. On the basis of the influence of the message embedding on the statistical distributions of alternating current (ac) discrete cosine transform (DCT) coefficients, we first develop a new steganalytic feature which is defined as the ratio between different ranges of the normalized ac coefficients histogram. Then a powerful blind detector is constructed with the proposed one-dimensional (1-D) feature. Extensive experimental results demonstrate that the proposed steganalyzer outperforms the existing state-of-the-art schemes significantly and even can detect the additive noise steganography effectively at a very low embedding rate. In addition, our method using a 1-D feature is not only practical and real-time, but also can provide a better control of the false positive rate and the false negative rate by adjusting the detection threshold. Moreover, the proposed feature can also be used to identify JPEG compression besides steganalysis, which indicates that our method has a great promise in practical applications.