Asymptotic methods in statistical theory
Asymptotic methods in statistical theory
Detecting LSB Steganography in Color and Gray-Scale Images
IEEE MultiMedia
Radiometric CCD camera calibration and noise estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Watermarking and Steganography
Digital Watermarking and Steganography
Clipped noisy images: Heteroskedastic modeling and practical denoising
Signal Processing
Steganography in Digital Media: Principles, Algorithms, and Applications
Steganography in Digital Media: Principles, Algorithms, and Applications
The 'Dresden Image Database' for benchmarking digital image forensics
Proceedings of the 2010 ACM Symposium on Applied Computing
Generalised category attack: improving histogram-based attack on JPEG LSB embedding
IH'07 Proceedings of the 9th international conference on Information hiding
Steganalysis by subtractive pixel adjacency matrix
IEEE Transactions on Information Forensics and Security
Classification of steganalysis techniques: A study
Digital Signal Processing
Advanced Statistical Steganalysis
Advanced Statistical Steganalysis
"Break our steganographic system": the ins and outs of organizing BOSS
IH'11 Proceedings of the 13th international conference on Information hiding
Statistical decision methods in hidden information detection
IH'11 Proceedings of the 13th international conference on Information hiding
A cover image model for reliable steganalysis
IH'11 Proceedings of the 13th international conference on Information hiding
On the generalized likelihood ratio test for a class of nonlineardetection problems
IEEE Transactions on Signal Processing
Detection of LSB steganography via sample pair analysis
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Detection of hiding in the least significant bit
IEEE Transactions on Signal Processing - Part II
Steganalysis for Markov cover data with applications to images
IEEE Transactions on Information Forensics and Security
Optimized Feature Extraction for Learning-Based Image Steganalysis
IEEE Transactions on Information Forensics and Security
Optimal statistical fault detection with nuisance parameters
Automatica (Journal of IFAC)
Performance Measures for Neyman–Pearson Classification
IEEE Transactions on Information Theory
Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data
IEEE Transactions on Image Processing
-Optimal Non-Bayesian Anomaly Detection for Parametric Tomography
IEEE Transactions on Image Processing
Adaptive Steganalysis of Least Significant Bit Replacement in Grayscale Natural Images
IEEE Transactions on Signal Processing
Steganalysis of LSB replacement using parity-aware features
IH'12 Proceedings of the 14th international conference on Information Hiding
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This paper studies the statistical detection of data hidden in the Least Significant Bits (LSB) plan of natural clipped images using the hypothesis testing theory. The main contributions are the following. First, this paper proposes to exploit the heteroscedastic noise model. This model, characterized by only two parameters, explicitly provides the noise variance as a function of pixel expectation. Using this model enhances the noise variance estimation and hence, allows the improving of detection performance of the ensuing test. Second, this paper introduces the clipped phenomenon caused by the limited dynamic range of the imaging device. Overexposed and underexposed pixels are statistically modeled and specifically taken into account to allow the inspecting of images with clipped pixels. While existing methods in the literature fail when the data is embedded in clipped images, the proposed detector still ensures a high detection performance. The statistical properties of the proposed GLRT are analytically established showing that this test is a Constant False Alarm Rate detector: it guarantees a prescribed false alarm probability.