Calibrated steganalysis of mp3stego in multi-encoder scenario
This work addresses a specific gap in mp3 steganalysis for security applications, but it is incremental as it builds on existing calibration techniques and focuses on a narrow domain.
The paper tackles the problem of mp3 steganalysis performance degradation due to differences in mp3 encoder implementations, proposing a new set of calibrated features based on quantization step analysis to address this issue, resulting in accurate encoder classification with only four features.
Comparing popularity of mp3 and wave with the amount of works published on each of them shows mp3 steganalysis has not found adequate attention. Furthermore, investigating existing works on mp3 steganalysis shows that a major factor has been overlooked. Experimenting with different mp3 encoders shows there are subtle differences in their outputs. This shows that mp3 standard has been implemented in dissimilar fashions, which in turn could degrade performance of steganalysis if it is not addressed properly. Additionally, calibration is a powerful technique which has not found its true potential for mp3 steganalysis. This paper tries to fill these gaps. First, we present our analysis on different encoders and show they can be classified quite accurately with only four features. Then, we propose a new set of calibrated features based on quantization step. To that end, we show quantization step is a band limited signal and steganography noise affects its high frequency components more prominently. By applying a low pass filter on quantization steps, we arrive at an estimation of quantization step, which in turn is used for calibrating the features.