Improving steganalysis by fusion techniques: a case study with image steganography
Transactions on Data Hiding and Multimedia Security I
Proceedings of the 10th ACM workshop on Multimedia and security
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
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A review of the audio and video steganalysis algorithms
Proceedings of the 48th Annual Southeast Regional Conference
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
Information Sciences: an International Journal
Steganalysis for MP3Stego using differential statistics of quantization step
Digital Signal Processing
VoIP steganography and its Detection—A survey
ACM Computing Surveys (CSUR)
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While image steganalysis has become a well researched domain in the last years, audio steganalysis still lacks a large scale attentiveness. This is astonishing since digital audio signals are, due to their stream-like composition and the high data rate, appropriate covers for steganographic methods. In this work one of the first case studies in audio steganalysis with a large number of information hiding algorithms is conducted. The applied trained detector approach, using a SVM (support vector machine) based classification on feature sets generated by fusion of time domain and Mel-cepstral domain features, is evaluated for its quality as a universal steganalysis tool as well as a application specific steganalysis tool for VoIP steganography (considering selected signal modifications with and without steganographic processing of audio data). The results from these evaluations are used to derive important directions for further research for universal and application specific audio steganalysis.