Embedding information in DCT coefficients based on average covariance

Embedding information in DCT coefficients based on average covarianc

Steganalysis of YASS using Huffman Length statistics

This work proposes two main contributions to statistical steganalysis of Yet Another Steganographic Scheme (YASS) in JPEG images. Firstly, this work presents a reliable blind steganalysis technique to predict YASS which is one of recent and least statistically detectable embedding scheme using only five features, four Huffman length statistics (H) and the ratio of file size to resolution (FR Index). Secondly these features are shown to be unique, accurate and monotonic over a wide range of settings for YASS and several supervised classifiers with the accuracy of prediction superior to most blind steganalyzers in vogue. Overall, the proposed model having Huffman Length Statistics as its linchpin predicts YASS with an average accuracy of over 94 percent