An active steganalysis approach for echo hiding based on Sliding Windowed Cepstrum

This paper presents an active steganalysis technique for echo hiding (EH). This approach can differentiate stego audios (with hidden message) from nature ones (without hidden message), and then extract sequential EH messages in stego audios without prior knowledge about the EH technique. The procedure of this algorithm can be simplified as follows: (i) Sliding Windowed Cepstrum (SWC) is obtained by employing a Sliding Window (SW) to move over the audio signal sample by sample. (ii) The echo detector is designed based on statistical analysis of the Cepstrum Peak Location Aggregation Degree (CPLAD). (iii) For stego signals, both echo delay and the range of segment length are estimated by exploring the changing rule of the SWC. (iv) The accurate estimation of segment length and synchronism position is acquired by the grid search algorithm. (v) Finally, the binary secret message can be extracted using the estimated parameters in the previous steps. The proposed method has been implemented and tested to extract the message which is embedded into audio clips by using EH techniques with different kernels. The experimental results show that the accuracy of extraction is no less than 90% when attenuation is greater than 0.45.