An Adaptive JPEG Double Compression Steganographic Scheme Based on Irregular DCT Coefficients Distribution

Abstract

Steganography is to embed secret information into digital media and minimize the distortion caused by data embedding. The JPEG is a widely used image compression format, and many JPEG images transmitted on the network are double compressed. Most of the existing steganography algorithms mainly use the single compressed images as the embedded carrier of secret information while rarely taking advantage of the double compressed images. However, the double compressed operation usually leads to changes in the statistical characteristics of images. Therefore, the minor changes caused by steganography can be confused by double compression operation to achieve the purpose of concealing embedding operation. This paper proposes a secure JPEG double compression (DC) steganographic scheme based on irregular discrete cosine transformation (DCT) and coefficients distribution (IDCD-JDS), which can obtain less statistical detectability. The minimum distortion function is designed according to the fact that the statistical distribution of the double compressed images has periodic peaks and valleys as well as multiple irregular intervals. By using the syndrome trellis coding (STC) to embed secret information, the modifications are limited to regions that are difficult to detect. The quality factors (QF) relationship between the first and second compression is further studied to explore the effective range for double compressed images so that the proposed algorithm can achieve better performance under different conditions. The experiments show that this scheme can reduce the embedding change by utilizing the inherent statistical distribution and irregular block complexity in double compressed images, and it performs better than the existing methods.