Digital images and human vision
Digital images and human vision
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Attacks on Steganographic Systems
IH '99 Proceedings of the Third International Workshop on Information Hiding
Detection of LSB Steganography via Sample Pair Analysis
IH '02 Revised Papers from the 5th International Workshop on Information Hiding
Shape Matching: Similarity Measures and Algorithms
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
Effective Steganalysis Based on Statistical Moments of Wavelet Characteristic Function
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume I - Volume 01
Reliable detection of LSB steganography in color and grayscale images
MM&Sec '01 Proceedings of the 2001 workshop on Multimedia and security: new challenges
Blind statistical steganalysis of additive steganography using wavelet higher order statistics
CMS'05 Proceedings of the 9th IFIP TC-6 TC-11 international conference on Communications and Multimedia Security
Detection of hiding in the least significant bit
IEEE Transactions on Signal Processing - Part II
Steganalysis using image quality metrics
IEEE Transactions on Image Processing
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)
Multimedia Tools and Applications
A new scheme for covert communication via 3G encoded speech
Computers and Electrical Engineering
Audio steganalysis based on lossless data-compression techniques
ICICS'12 Proceedings of the 14th international conference on Information and Communications Security
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Steganography can be used to hide information in audio media both for the purposes of digital watermarking and establishing covert communication channels. Digital audio provides a suitable cover for high-throughput steganography as a result of its transient and unpredictable characteristics. Distortion measure plays an important role in audio steganalysis - the analysis and classification method of determining if an audio medium is carrying hidden information. In this paper, we propose a novel distortion metric based on Hausdorff distance. Given an audio object xwhich could potentially be a stego-audio object, we consider its de-noised version x茂戮驴 as an estimate of the cover-object. We then use Hausdorff distance to measure the distortion from xto x茂戮驴. The distortion measurement is obtained at various wavelet decomposition levels from which we derive high-order statistics as features for a classifier to determine the presence of hidden information in an audio signal. Extensive experimental results for the Least Significant Bit (LSB) substitution based steganography tool show that the proposed algorithm has a strong discriminatory ability and the performance is significantly superior to existing methods. The proposed approach can be easily applied to other steganography tools and algorithms.