Spectrum Steganalysis of WAV Audio Streams

Authors:
Qingzhong Liu;Andrew H. Sung;Mengyu Qiao
Affiliations:
Computer Science and Engineering Department, and Institute for Complex Additive Systems Analysis, New Mexico Tech, Socorro, USA NM 87801;Computer Science and Engineering Department, and Institute for Complex Additive Systems Analysis, New Mexico Tech, Socorro, USA NM 87801;Computer Science and Engineering Department,
Venue:
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Year:
2009

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Abstract

In this paper, we propose an audio steganalysis method called reference based Fourier Spectrum Steganalysis. The mean values and the standard deviations of the high frequency spectrum of the second and high order derivatives are extracted from the testing signals and the reference versions. A Support Vector Machine (SVM) is employed to discriminate the unadulterated carrier signals and the steganograms wherein covert messages were embedded. Experimental results show that our method delivers very good performance and holds great promise for effective detection of steganograms produced by Hide4PGP, Invisible Secrets, S-tools4 and Steghide.