  In this letter, we present a novel and extremely fast steganalysis method of
Voice over IP (VoIP) streams, driven by the need for a quick and accurate
detection of possible steganography in VoIP streams. We firstly analyzed the
correlations in carriers. To better exploit the correlation in code-words, we
mapped vector quantization code-words into a semantic space. In order to
achieve high detection efficiency, only one hidden layer is utilized to extract
the correlations between these code-words. Finally, based on the extracted
correlation features, we used the softmax classifier to categorize the input
stream carriers. To boost the performance of this proposed model, we
incorporate a simple knowledge distillation framework into the training
process. Experimental results show that the proposed method achieves
state-of-the-art performance both in detection accuracy and efficiency. In
particular, the processing time of this method on average is only about 0.05\%
when sample length is as short as 0.1s, attaching strong practical value to
online serving of steganography monitor.
