Research Article
Year 2017,
Volume: 29 Issue: 2, 75 - 79, 01.10.2017
Abstract
Son yıllarda, dijital verilerin kullanımının önemli ölçüde artması ile dijital ortam verilerinin gizli haberleşme için kullanılması oldukça yaygınlaşmıştır. Bununla birlikte, dijital verilerdeki gizli mesajın tespiti (steganaliz) çalışmaları da aynı ölçüde önem kazanmaktadır. Bu çalışmanın amacı, literatürde konuşma işleme uygulamalarında yaygın olarak kullanılan Gauss karışım modeli (GKM) sınıflandırıcısı ve Mel-frekansı kepstrum katsayıları (MFKK) özniteliklerini kullanarak dijital ses (konuşma) dosyalarındaki gizli mesaj varlığını belirlemektir. 4380 adet konuşma sinyalinin kullanıldığı deneysel çalışmalardan MFKK öznitelikleri ve GKM sınıflandırıcısının gizli mesaj tespiti probleminde yaygın olarak kullanılan destek vektör makineleri (DVM) sınıflandırıcısından daha iyi sonuç verdiği görülmektedir.
References
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Year 2017,
Volume: 29 Issue: 2, 75 - 79, 01.10.2017
Abstract
References
- 1. Petitcolas, F. A. P., Anderson, R.J., and Kuhn, M.G. (1999). Information Hiding--A Survey. Proceedings of the IEEE, 87(7): 1062-1078.
- 2. Mavel, L.M. (2005). Information Hiding: Steganography and Watermarking. Optical and Digital Techniques for Information Security, New York, Springer New York, 113-133.
- 3. Böhme, R. (2010). Principles of Modern Steganography and Steganalysis. Information Security and Cryptography, 11-77.
- 4. Ghasemzade, H., Khass, T.M. and Arjmandi, M. K. (2016). Audio steganalysis based on reversed psychoacoustic model of human hearing. Digital Signal Processing, 51: 133-141
- 5. Özer, H., Avcıbaş, İ., Sankur, B. and Memon, N.(2003). Steganalysis of audio based on audio quality metrics. Electronic Imaging, International Society for Optics and Photonics.
- 6. Burges, C. J. C. (1998). A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery , 2: 121-167.
- 7. Johnson, K.M., Lyu, S. and Farid, H.(2005). Steganalysis of Recorded Speech. Electronic Imaging, International Society of Optics and Photonics.
- 8. Ru, X.-M., Zhang, H.-J. and Huang, X. (2005). Steganalysis of audio: attacking the steghide. International Conference on Machine Learning and Cybernetics.
- 9. Fu, J.-W., Qi, Y.-C. and Yuan, J.-S. (2007). Wavelet domain audio steganalysis based on statistical moments and PCA. International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR).
- 10. Reynolds, D.A. and Rose, C. R. (1995). Robust Text-Independent Speaker Identification Using Gaussian Mixture Speaker Models. IEEE Transactions on Speech and Audio Processing, 3(1): 72-83.
- 11. Reynolds, D.A., Quatieri, T.F., Dunn, R.B. (2000). Speaker Verification Using Adapted Gaussian Mixture Models. Digital Signal Processing 10(1-3):19-41
- 12. “Steghide,” [Çevrimiçi]. Available: http://steghide.sourceforge.net/index.php. [02 Şubat 2017 tarihinde erişilmiştir].
- 13. Davis, S. B. and Mermelstein, P.(1980). Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences. IEEE Transactions on Acoustics, Speech, and Signal Processing, 28(4): 357-366.
- 14. Chang, C.-C. and Lin, C.J.(2011). LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2(3): 1-27
There are 14 citations in total.
Details
| Journal Section | MBD |
|---|---|
| Authors | |
| Publication Date | October 1, 2017 |
| Submission Date | February 13, 2017 |
| Published in Issue | Year 2017 Volume: 29 Issue: 2 |