Spectrum Steganalysis of WAV Audio Streams
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Novel stream mining for audio steganalysis
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Temporal derivative-based spectrum and mel-cepstrum audio steganalysis
IEEE Transactions on Information Forensics and Security
A review of the audio and video steganalysis algorithms
Proceedings of the 48th Annual Southeast Regional Conference
Derivative-based audio steganalysis
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A new scheme for covert communication via 3G encoded speech
Computers and Electrical Engineering
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Audio steganalysis has attracted more attentions recently. Phase steganalysis is one of the most challenging research fields.In this paper, a novel algorithm to detect phase coding steganography in audio signal is proposed. It is based on analysis of the phase discontinuities, and can be described as follows. Firstly, it takes FFT transform of special segment of audio and unwraps the phases of each audio sample, then extracts the phase difference between neighboring samples. Secondly, in order to monitor the change of phase difference, it calculates the five statistical features of phase difference for steganalysis. Thirdly, the SVM classifier is utilized for classification. All of the 800 various audios are trained and tested in our experimental work. With various embedding parameters for training and testing audios, the proposed algorithm can achieve a good classification,and the correct rate of detecting is up to 95%.