This paper presents a novel methodology for statistical detection of Least Significant Bits (LSB) matching steganography. It proposes to exploit a statistical model of natural images adjacent pixels difference. In this paper, the detection problem is first addressed in a theoretical context when cover image parameters are known. The most powerful likelihood ratio test (LRT) is designed and its statistical performances are analytically expressed. Then, for a practical case of unknown image analysis, an estimation of distribution parameters is proposed to designed a test whose performance are also analytically established. Numerical results on a large image database shows the relevance of proposed methodology.