Spread Spectrum Steganography Detection Algorithm Based on Wavelet Singularity Analysis
Jiazhen Wang · Jisuanji gongcheng · 2009
Aiming at the shortcoming that spread spectrum steganography breaks image local stationarity,this paper presents a detection algorithm for spread spectrum steganography based on wavelet singularity analysis.It extracts 8 dimension feature vector as the input vector of Fisher classifier by analyzing the changes of wavelet coefficients modulus maximum on different scales of images to be detected,and uses a mass of samples to train Fisher classifier.The detection and attacking experimental results prove that the average detection rate of the algorithm is more than 80%,and it can detect the spectrum range in which the secret message is hidden and implement effective attack,which lays the foundation for extracting the stego message.