Determining the stego algorithm for JPEG images

The goal of forensic steganalysis is to detect the presence of embedded data and to eventually extract the secret message. A necessary step towards extracting the data is determining the steganographic algorithm used to embed the data. In the paper, we construct blind classifiers capable of detecting steganography in JPEG images and assigning stego images to six popular JPEG embedding algorithms. The classifiers are support vector machines that use 23 calibrated DCT feature calculated from the luminance component