Hidden information detection based on quantized Laplacian distribution

The goal of this paper is to propose the optimal statistical test based on the modeling of discrete cosine transform (DCT) coefficients with a quantified Laplacian distribution. This paper focuses on the detection of hidden information embedded in bits of the DCT coefficients of a JPEG image. This problem is difficult, in terms of statistical decision, for two main reasons: first, the number of DCT coefficients used to conceal the hidden bits is random; second, the JPEG image compression induces a strong quantization of DCT coefficients. The proposed test explicitly takes into account the randomness of the number of DCT coefficients used. It maximizes the probability of hidden information detection by ensuring a prescribed level of false alarm.