Reference-free differential histogram-correlative detection of steganography: performance analysis

<span lang="EN-US">Recent <span>research has demonstrated the effectiveness of utilizing neural networks for detect tampering in images. However, because accessing a database is complex, which needed classification process to tampering, reference-free steganalysis attracted attention. In recent work, an approach least significant bit (LSB) been presented based on analyzing derivatives histogram correlation. this paper, we further examine strategy other steganographic methods. Detecting image spatial domain, such as steganography. It found that above could be applied successfully kinds steganography with different orders histogram-correlation derivatives. Also, limits ratio stego-image cover are considered, where very small ratios can escape detection method unless </span> modified.</span>