Statistical Model of Quantized DCT Coefficients: Application in the Steganalysis of Jsteg Algorithm

• Published in: IEEE transactions on image processing Vol. 23; no. 5; pp. 1980 - 1993
• Main Authors: Thai, Thanh Hai, Cogranne, Remi, Retraint, Florent
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.05.2014; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Algorithms; Applied sciences; Computer Science; Cryptography; Detection, estimation, filtering, equalization, prediction; Digital cameras; Discrete cosine transforms; Economic models; Exact sciences and technology; Fittings; Image coding; Image color analysis; Image Processing; Information, signal and communications theory; JPEG encoders-decoders; Laplace equations; Mathematical model; Mathematical models; Random variables; Signal and communications theory; Signal processing; Signal, noise; Statistical analysis; Telecommunications and information theory; Transform coding; discrete cosine transform; hypothesis testing; JPEG compression; Digital image model; steganalysis; Performance evaluation; Image processing; Stéganography; Image compression; Digital image; Algorithm; Hypothesis test; Image coding; Accuracy; Steganalysis; Information protection; Statistical model; Likelihood ratio test; Signal processing; Numerical simulation; Maximum likelihood; Discrete cosine transforms
• ISSN: 1057-7149; 1941-0042; 1941-0042
• DOI: 10.1109/TIP.2014.2310126

The goal of this paper is to propose a statistical model of quantized discrete cosine transform (DCT) coefficients. It relies on a mathematical framework of studying the image processing pipeline of a typical digital camera instead of fitting empirical data with a variety of popular models proposed in this paper. To highlight the accuracy of the proposed model, this paper exploits it for the detection of hidden information in JPEG images. By formulating the hidden data detection as a hypothesis testing, this paper studies the most powerful likelihood ratio test for the steganalysis of Jsteg algorithm and establishes theoretically its statistical performance. Based on the proposed model of DCT coefficients, a maximum likelihood estimator for embedding rate is also designed. Numerical results on simulated and real images emphasize the accuracy of the proposed model and the performance of the proposed test.