On Advances in Statistical Modeling of Natural Images
Journal of Mathematical Imaging and Vision
Statistical characterisation of MP3 encoders for steganalysis
Proceedings of the 2004 workshop on Multimedia and security
Image complexity and feature mining for steganalysis of least significant bit matching steganography
Information Sciences: an International Journal
Gene selection by sequential search wrapper approaches in microarray cancer class prediction
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Challenges for future intelligent systems in biomedicine
Temporal derivative-based spectrum and mel-cepstrum audio steganalysis
IEEE Transactions on Information Forensics and Security
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
An improved approach to steganalysis of JPEG images
Information Sciences: an International Journal
A Markov process based approach to effective attacking JPEG steganography
IH'06 Proceedings of the 8th international conference on Information hiding
Information Sciences: an International Journal
Pros and cons of mel-cepstrum based audio steganalysis using SVM classification
IH'07 Proceedings of the 9th international conference on Information hiding
Steganalysis of LSB matching based on statistical modeling of pixel difference distributions
Information Sciences: an International Journal
Neighboring joint density-based JPEG steganalysis
ACM Transactions on Intelligent Systems and Technology (TIST)
Derivative-based audio steganalysis
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Steganalysis of content-adaptive steganography in spatial domain
IH'11 Proceedings of the 13th international conference on Information hiding
Improving steganalysis by fusion techniques: a case study with image steganography
Transactions on Data Hiding and Multimedia Security I
Steganalysis using higher-order image statistics
IEEE Transactions on Information Forensics and Security
Analysis of multiresolution image denoising schemes using generalized Gaussian and complexity priors
IEEE Transactions on Information Theory
On the limits of steganography
IEEE Journal on Selected Areas in Communications
Statistical texture characterization from discrete wavelet representations
IEEE Transactions on Image Processing
Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance
IEEE Transactions on Image Processing
Steganalysis using image quality metrics
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Editorial: Guest editorial: Special issue on data mining for information security
Information Sciences: an International Journal
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MP3, one of the most widely used digital audio formats, provides a high compression ratio with faithful quality. The widespread use enables MP3 audio files to become excellent covers to carry hidden information in audio steganography on the Internet. Our research, however, indicates that there are few steganalysis methods proposed to detect audio steganograms and that steganalysis methods for the information-hiding behavior in MP3 audio are particularly scarce. In this paper we propose a comprehensive approach to steganalysis of MP3 audio files by deriving a combination of features from quantized MDCT coefficients. We design frequency-based subband moment statistical features, accumulative Markov transition features, and accumulative neighboring joint density features on second-order derivatives. We also model the distortion by extracting the shape parameters of generalized Gaussian density from individual frames. Different feature selection algorithms are applied to improve detection accuracy. Signal complexity and modification density are introduced to provide a comprehensive evaluation. Experimental results show that our approach is successful in discriminating MP3 covers and the steganograms generated by the steganographic tool, MP3Stego, in each category of signal complexity, especially for the audio streams with high signal complexities that are generally more difficult to steganalyze.