BibTex RIS Kaynak Göster

Konuşma Sesleri Steganalizine Gecikmeli Vektör Varyans Metodunu Kullanan Yeni Bir Yaklaşım

Yıl 2014, Cilt: 19 Sayı: 1, 27 - 36, 01.04.2014

Öz

We investigate the use of delay vector variance-based features for recorded speech steganalysis. Considering that data hiding within a speech signal distorts the properties of the original speech signal, we design a steganalyzer that uses surrogate data based delay vector variance (DVV) features to detect the existence of a stego-signal. We evaluate the performance of the proposed DVV features as steganalyzer with numerical results

Kaynakça

  • Westfeld, A.P. (2003). Detecting Low Embedding Rates, Fabien A. P. Petitcolas (Ed.):
  • Information Hiding. 5th International Workshop, IH 2002 Noordwijkerhout, pp. 324–339,
  • Springer-Verlag Berlin Heidelberg..
  • Fridrich, J. and Goljan, M. (2002). Practical Steganalysis of Digital Images - State of the Art,
  • Proc. SPIE Photonics West, Vol. 4675, pp. 1—13.
  • Johnson, M.K., Lyu, S. and Farid, H. (2005). Steganalysis of Recorded Speech, Proc. SPIE
  • Symposium on Electronic Imaging, San Jose, CA.
  • Westfeld, A.P. and Pfitzmann, A. (1999). Attacks on steganographic systems, Information
  • Hiding, LNCS 1768, pp. 61-66, Springer-Verlag Heidelberg.
  • Koçal, O.H., Yürüklü, E. and Avcıbaş, İ. (2008). Chaotic-type features for Speech
  • Steganalysis, IEEE Transactions on Information Forensics and Security, Vol. 3, Issue 4, pp. 651- 661.
  • Altun, O., Sharma, G., Celik, M., Sterling, M., Titlebaum, E. and Bocko, M. (2005).
  • Morphological Steganalysis of Audio Signals and the Principle of Diminishing Marginal
  • Distortions”, IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, Proceedings. (ICASSP
  • '05), Vol. 2, pp. 21- 24.
  • Ozer, H., Avcibas, I.,, Sankur, B. and Memon, N. (2003). Steganalysis of Audio Based on
  • Audio Quality Metrics, Proc. SPIE, Security and Watermarking of Multimedia Contents V, Vol. 5020, pp. 55-66.
  • Kokkinos, I. and Maragos, P. (2005). Nonlinear Speech Analysis Using Models for Chaotic
  • Systems, IEEE Transactions on Speech and Audio Processing, Vol. 13, No. 6, pp. 1098-1109.
  • Banbrook, M. and McLaughlin, S., (1999). Speech Characterization and Synthesis by
  • Nonlinear Methods”, IEEE Transactions on Speech and Audio Processing, Vol. 7, No. 1, pp. 1- 17.
  • Theiler, J., Eubank, S., Longtin, A., Galdrikian, B. and Farmer, J. D. (1992). Testing for
  • Nonlinearity in Time Series: The Method of Surrogate Data, Physica D 58. pp. 77 - 94.
  • Gautama, T., Mandic, D.P. and Van Hulle, M.M. (2003). Indications of nonlinear structures
  • in brain electrical activity, Physical Review E, Vol. 67, No. 046204.
  • Schreiber, T. and Schmitz, A. (1997). Discrimination power of measures for nonlinearity in
  • a time series, Phys. Rev. E, Vol:55. pp. 5443-5447.
  • Gautama, T., Mandic, D.P. and Van Hulle, M.M. (2004). A Novel Method for Determining
  • the Nature of Time Series, IEEE Transactions On Bıomedical Engineering, Vol. 51, No. 5.
  • Simmons, G. J. (1984). Prisoners' Problem and the Subliminal Channel (The), CRYPTO83
  • Advances in Cryptology, pp. 51-67.
  • Bender, W., Gruhl, D., Morimoto, N. and Lu, A. (1996). Techniques for data hiding, IBM
  • Systems Journal, vol. 35, no: 3&4, pp. 313-336.
  • Fridrich, J. and Goljan, M. (2003). Digital Image Steganography Using Stochastic
  • Modulation, Proc. SPIE Electronic Imaging, Santa Clara, CA, pp. 191-202.
  • Cox., I. J., Kilian, J., Leighton, F.T. and Shamoon, T. (1997). Secure spread spectrum
  • watermarking for multimedia, IEEE Tr. Image Proc., vol 6, pp. 1673 – 1687.
  • www.steganos.com,. Access Date: 23.Nov.2011, Subject: Steganos.
  • www.petitcolas.net/fabien/ steganography/mp3stego,Access Date: 12.Sep.2011, Subject: Mp3stego.
  • http://steghide.sourceforge.net, Access Date: 13.Sep.2011, Subject: S. Hetzl.
  • www.heinz-repp.onlinehome.de/Hide4PGP.htm, Access Date: 12.Sep.2011, Subject: Hide4PGP
  • http://www.mpi.nl/world/tg/corpora/timit/timit.html, Access Date: 05.Jul.2011, Subject: TIMIT Speech Database
  • Kennel, M. B. and Abarbanel, H. D. I. (2002). False neighbors and false strands: A reliable minimum embedding dimension algorithm”, Physical Review E, Vol. 66, 026209.
  • Hilborn, R. (2000). Chaos and Nonlinear Dynamics, Oxford University Press, 2. ed.
  • Hegger, R., Kantz, H. and Schreiber, T. (1999). Practical Implementation of Nonlinear Time Series Methods: The TISEAN Package, Chaos, Vol. 9, pp. 413-435.
  • Pudil, P., Novovicova, J. and Kittler, J. (1994). Floating Search Methods in Feature Selection, Pattern Recognition Lett. Vol 15, pp. 1119-1125.
  • http://eewww.eng.ohio-state.edu/~maj/osu_svm/, Access Date: 24.Sep.2011, Subject: OSU- SVM Matlab Toolbox.
  • Özer, H., Sankur, B., Memon, N. and Avcıbaş, İ. (2006). Detection of Audio Covert Channels Using Statistical Footprints of Hidden Messages, Digital Signal Processing, Vol.16, pp. 389-401.
  • Makale 19.11.2013 tarihinde alınmış, 07.12.2013 tarihinde düzeltilmiş, 09.12.2013 tarihinde kabul edilmiştir.

A New Approach For Speech Audio Steganalysis Using Delay Vector Variance Method

Yıl 2014, Cilt: 19 Sayı: 1, 27 - 36, 01.04.2014

Öz

Bu çalışmada gecikmeli vektör varyans metodunun, kayıt edilmiş konuşma seslerinin steganalizinde kullanımı araştırılmıştır. Konuşma sinyali içerisine veri gizlemenin orijinal ses verisinin özelliklerini bozacağı gerçeğinden göz önünde bulundurarak, vekil verileri kullanan gecikmeli vektör varyans (DVV) özelliklerindeki değişimi kontrol eden ve böylece stego-sinyalin varlığını tespit etmeye çalışan yeni bir steganalizör tasarlanmıştır. DVV özelliklerini baz alan önerilen steganalizörün performans başarımı ise nümerik değerlerle verilmiştir

Kaynakça

  • Westfeld, A.P. (2003). Detecting Low Embedding Rates, Fabien A. P. Petitcolas (Ed.):
  • Information Hiding. 5th International Workshop, IH 2002 Noordwijkerhout, pp. 324–339,
  • Springer-Verlag Berlin Heidelberg..
  • Fridrich, J. and Goljan, M. (2002). Practical Steganalysis of Digital Images - State of the Art,
  • Proc. SPIE Photonics West, Vol. 4675, pp. 1—13.
  • Johnson, M.K., Lyu, S. and Farid, H. (2005). Steganalysis of Recorded Speech, Proc. SPIE
  • Symposium on Electronic Imaging, San Jose, CA.
  • Westfeld, A.P. and Pfitzmann, A. (1999). Attacks on steganographic systems, Information
  • Hiding, LNCS 1768, pp. 61-66, Springer-Verlag Heidelberg.
  • Koçal, O.H., Yürüklü, E. and Avcıbaş, İ. (2008). Chaotic-type features for Speech
  • Steganalysis, IEEE Transactions on Information Forensics and Security, Vol. 3, Issue 4, pp. 651- 661.
  • Altun, O., Sharma, G., Celik, M., Sterling, M., Titlebaum, E. and Bocko, M. (2005).
  • Morphological Steganalysis of Audio Signals and the Principle of Diminishing Marginal
  • Distortions”, IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, Proceedings. (ICASSP
  • '05), Vol. 2, pp. 21- 24.
  • Ozer, H., Avcibas, I.,, Sankur, B. and Memon, N. (2003). Steganalysis of Audio Based on
  • Audio Quality Metrics, Proc. SPIE, Security and Watermarking of Multimedia Contents V, Vol. 5020, pp. 55-66.
  • Kokkinos, I. and Maragos, P. (2005). Nonlinear Speech Analysis Using Models for Chaotic
  • Systems, IEEE Transactions on Speech and Audio Processing, Vol. 13, No. 6, pp. 1098-1109.
  • Banbrook, M. and McLaughlin, S., (1999). Speech Characterization and Synthesis by
  • Nonlinear Methods”, IEEE Transactions on Speech and Audio Processing, Vol. 7, No. 1, pp. 1- 17.
  • Theiler, J., Eubank, S., Longtin, A., Galdrikian, B. and Farmer, J. D. (1992). Testing for
  • Nonlinearity in Time Series: The Method of Surrogate Data, Physica D 58. pp. 77 - 94.
  • Gautama, T., Mandic, D.P. and Van Hulle, M.M. (2003). Indications of nonlinear structures
  • in brain electrical activity, Physical Review E, Vol. 67, No. 046204.
  • Schreiber, T. and Schmitz, A. (1997). Discrimination power of measures for nonlinearity in
  • a time series, Phys. Rev. E, Vol:55. pp. 5443-5447.
  • Gautama, T., Mandic, D.P. and Van Hulle, M.M. (2004). A Novel Method for Determining
  • the Nature of Time Series, IEEE Transactions On Bıomedical Engineering, Vol. 51, No. 5.
  • Simmons, G. J. (1984). Prisoners' Problem and the Subliminal Channel (The), CRYPTO83
  • Advances in Cryptology, pp. 51-67.
  • Bender, W., Gruhl, D., Morimoto, N. and Lu, A. (1996). Techniques for data hiding, IBM
  • Systems Journal, vol. 35, no: 3&4, pp. 313-336.
  • Fridrich, J. and Goljan, M. (2003). Digital Image Steganography Using Stochastic
  • Modulation, Proc. SPIE Electronic Imaging, Santa Clara, CA, pp. 191-202.
  • Cox., I. J., Kilian, J., Leighton, F.T. and Shamoon, T. (1997). Secure spread spectrum
  • watermarking for multimedia, IEEE Tr. Image Proc., vol 6, pp. 1673 – 1687.
  • www.steganos.com,. Access Date: 23.Nov.2011, Subject: Steganos.
  • www.petitcolas.net/fabien/ steganography/mp3stego,Access Date: 12.Sep.2011, Subject: Mp3stego.
  • http://steghide.sourceforge.net, Access Date: 13.Sep.2011, Subject: S. Hetzl.
  • www.heinz-repp.onlinehome.de/Hide4PGP.htm, Access Date: 12.Sep.2011, Subject: Hide4PGP
  • http://www.mpi.nl/world/tg/corpora/timit/timit.html, Access Date: 05.Jul.2011, Subject: TIMIT Speech Database
  • Kennel, M. B. and Abarbanel, H. D. I. (2002). False neighbors and false strands: A reliable minimum embedding dimension algorithm”, Physical Review E, Vol. 66, 026209.
  • Hilborn, R. (2000). Chaos and Nonlinear Dynamics, Oxford University Press, 2. ed.
  • Hegger, R., Kantz, H. and Schreiber, T. (1999). Practical Implementation of Nonlinear Time Series Methods: The TISEAN Package, Chaos, Vol. 9, pp. 413-435.
  • Pudil, P., Novovicova, J. and Kittler, J. (1994). Floating Search Methods in Feature Selection, Pattern Recognition Lett. Vol 15, pp. 1119-1125.
  • http://eewww.eng.ohio-state.edu/~maj/osu_svm/, Access Date: 24.Sep.2011, Subject: OSU- SVM Matlab Toolbox.
  • Özer, H., Sankur, B., Memon, N. and Avcıbaş, İ. (2006). Detection of Audio Covert Channels Using Statistical Footprints of Hidden Messages, Digital Signal Processing, Vol.16, pp. 389-401.
  • Makale 19.11.2013 tarihinde alınmış, 07.12.2013 tarihinde düzeltilmiş, 09.12.2013 tarihinde kabul edilmiştir.
Toplam 49 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Araştırma Makaleleri
Yazarlar

Emrah Yürüklü Bu kişi benim

Osman Hilmi Koçal Bu kişi benim

Erdoğan Dilaveroğlu Bu kişi benim

Yayımlanma Tarihi 1 Nisan 2014
Gönderilme Tarihi 19 Aralık 2014
Yayımlandığı Sayı Yıl 2014 Cilt: 19 Sayı: 1

Kaynak Göster

APA Yürüklü, E., Koçal, O. H., & Dilaveroğlu, E. (2014). A New Approach For Speech Audio Steganalysis Using Delay Vector Variance Method. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, 19(1), 27-36. https://doi.org/10.17482/uujfe.19395
AMA Yürüklü E, Koçal OH, Dilaveroğlu E. A New Approach For Speech Audio Steganalysis Using Delay Vector Variance Method. UUJFE. Nisan 2014;19(1):27-36. doi:10.17482/uujfe.19395
Chicago Yürüklü, Emrah, Osman Hilmi Koçal, ve Erdoğan Dilaveroğlu. “A New Approach For Speech Audio Steganalysis Using Delay Vector Variance Method”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 19, sy. 1 (Nisan 2014): 27-36. https://doi.org/10.17482/uujfe.19395.
EndNote Yürüklü E, Koçal OH, Dilaveroğlu E (01 Nisan 2014) A New Approach For Speech Audio Steganalysis Using Delay Vector Variance Method. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 19 1 27–36.
IEEE E. Yürüklü, O. H. Koçal, ve E. Dilaveroğlu, “A New Approach For Speech Audio Steganalysis Using Delay Vector Variance Method”, UUJFE, c. 19, sy. 1, ss. 27–36, 2014, doi: 10.17482/uujfe.19395.
ISNAD Yürüklü, Emrah vd. “A New Approach For Speech Audio Steganalysis Using Delay Vector Variance Method”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 19/1 (Nisan 2014), 27-36. https://doi.org/10.17482/uujfe.19395.
JAMA Yürüklü E, Koçal OH, Dilaveroğlu E. A New Approach For Speech Audio Steganalysis Using Delay Vector Variance Method. UUJFE. 2014;19:27–36.
MLA Yürüklü, Emrah vd. “A New Approach For Speech Audio Steganalysis Using Delay Vector Variance Method”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, c. 19, sy. 1, 2014, ss. 27-36, doi:10.17482/uujfe.19395.
Vancouver Yürüklü E, Koçal OH, Dilaveroğlu E. A New Approach For Speech Audio Steganalysis Using Delay Vector Variance Method. UUJFE. 2014;19(1):27-36.

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