Kernel Fisher discriminant for steganalysis of JPEG hiding methods

Abstract

The use of kernel Fisher discriminants is used to detect the presence of JPEG based hiding methods. The feature vector for the kernel discriminant is constructed from the quantized DCT coefficient indices. Using methods developed in kernel theory a classifier is trained in a high dimensional feature space which is capable of discriminating original from stegoimages. The algorithm is tested on the F5 hiding method.