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Ideal Steganography Scenario: Calculation of Capacities of Carrier Images, OPA Method in Frequency-Based Steganography

Year 2018, , 12 - 21, 26.06.2018
https://doi.org/10.30801/acin.358076

Abstract

In this study, digital image steganography, a branch of
steganography, and DCT (Discrete Cosine Transform) and DWT (Discrete Wavelet Transform,
frequency-based steganography methods that are a sub-branch of it, are
mentioned. Methods such as MSE (Mean Squared Error), PSNR (Peak Signal Noise
Ratio) which are performance calculation parameters of steganographic methods
are explained and the methods of calculating image capacity like KL-Divergence,
JS-Divergence and QTS (Quard Tree Segmentation) for increasing the values of
these parameters are mentioned. This study explains the OPAP (Optimum Pixel
Adjustment Process) method, which allows the existing capacity in the pictures
to be further increased, in detail and provides an ideal steganography
scenario. Here, we made use of the ability of the DWT to extract low frequency
and bands suitable for data hiding and the use of the LSB method by obtaining
the feature coefficients of DCT in these bands.. In addition, this scenario has
been tried and consequently reached the result that the images with higher data
concealment capacity than QTS have higher PSNR values.

References

  • Holub, V., Fridrich, J., Denemark, T. (2014). Universal distortion function for steganography in an arbitrary domain, EURASIP Journal on Information Security, 2014(1), s.11-19.
  • Sajedi, H. (2016). Steganalysis based on steganography pattern discovery. Journal of Information Security and Applications, 30, 3-14.
  • Yaghmaee, F., Jamzad M.(2010). Estimating watermarking capacity in gray scale ımages based on ımage complexity , EURASIP Journal on Advances in Signal Processing, ss. 20102010:851920, doi: 10.1155/2010/851920.
  • Subhedar, M.S., Mankar, V.H. (2014). Current status and key issues in image steganography: A survey, Computer Science Review, 13, ss. 95-113.
  • Challita, K., Farhat, H. (2011). Combining steganography and cryptography: new directions. International Journal on New Computer Architectures and Their Applications, 1(1), ss.199-208.
  • Verma, N.(2011). Review of steganography techniques, International Conference and Workshop on Emerging Trends in Technology (ICWET 2011)–TCET, Mumbai, India
  • Zeki, A.M., Ibrahim, A.A., Manaf, A.A.(2012). Steganographic software:analysis and implementation, International Journal Of Computers And Communications, 6(1).
  • Hemalatha, S., Acharya U. D., Renuka, A., Kamath, P.R.(2012). A Novel color image steganography using discrete wavelet transform, CCSEIT-12, October 26-28, 2012, Coimbatore, India.
  • Suvarna P., Chandel, G.S.(2013). Performance analysis of steganography based on 5-wavelet families by 4 levels -dwt suvarna, International Journal of Advance Research in Computer Science and Management Studies, 1(7), ss. 20-33.
  • Dhawale, C. A., Hegadi, R., Jambhekar, N.D.(2014). Performance analysis of digital ımage steganographic algorithm. ICTCS '14, Kasım 14 – 16, 2014, Udaipur, Rajasthan, India, ACM 978-1-4503-3216-3/14/11.
  • Sujatha, P., Purushothaman, S., Rajeswari, R. (2014). Performance study of combined artificial neural network algorithms for ımage steganalysis, In Proceedings of International Conference on Internet Computing and Information Communications, ss. 441-451, Springer India.
  • Liu, Y., Liu, Y., Wu, S., Zhong, S. (2015). What Makes the Stego Image Undetectable? ICIMCS ’15, Ağustos 19-21, 2015, Zhangjiajie, Hunan, China, ACM. ISBN 978-1-4503-3528-7/15/08.
  • Hemalatha, S., Acharya, U.D., Renuka, A.(2015). Wavelet transform based steganography technique to hide audio signals in image, Procedia Computer Science, 47, ss.272-281.
  • Provos, N., Honeyman, P. (2001). Detecting steganographic content on the internet, Center for Information Technology Integration, NDSS 2002, San Diego.
  • Haşiloğlu, A. (2001). Dalgacık dönüşümü ve yapay sinir ağları ile döndürmeye duyarsız doku analizi ve sınıflandırma, Turk J. Engin Environ Sci, 25, ss.405-413.
  • Dalvi, A., Kamathe, R.S. (2015). Color ımage steganography by using dual wavelet transform (DWT SWT). International Journal of Scientific Engineering and Research (IJSER), 3(7), ss.25-41.
  • Bera, S., Dewangan, U., Sharma, M. (2013). Development and analysis of stego ımage using discrete wavelet transform, International Journal of Science and Research (IJSR), India Online ISSN: 2319-7064.
  • Cheddad A., J. Condell, K., Kevitt, P.(2010). Digital ımage steganography: survey and analysis of current methods, Signal Processing, 90(3), ss.727-752.
  • Peterson, A.K. (2005). Introduction to Basic Measures of a Digital Image for Pictorial Collections, Prints & Photographs Division, Library of Congress, Washington, DC, ss. 20540-4720.
  • Muhsin, Z. F., Rehman, A., Altameem, A., Saba, T., & Uddin, M. (2014). Improved quadtree image segmentation approach to region information. The Imaging Science Journal, 62(1), ss. 56-62.
  • Lin,Y-C, Li, T-S (2011). Reversible image data hiding using quad-tree segmentation and histogram shifting, Journal of Multimedia, 6 (4), ss. 349-358.
  • Kaur, S., Goel, N. (2015). Segmentation and block based image steganography using optimal pixel adjustment process and identical approach, 2nd International Conference on Recent Advances in Engineering & Computational Sciences (RAECS), Chandigarh, 2015, ss. 1-5.
  • Nithya , R. K., Nehru, C.P., Ubramanıam, T.B.(2014). Optimal pixel adjustment based reversible steganography, (IJITR) International Journal Of Innovatıve Technology And Research, 2 (3), 2014, ss. 963–966.
  • Demirci, B. (2016). Görüntü steganografi metotları ve performanslarının karşılaştırılması (Doktora Tezi, Selçuk Üniversitesi Fen Bilimleri Enstitüsü).
  • Kaya, H. V. (2015). Watermarking in medical images by using DWT, DCT, DFT and lSB algorithms (Doktora Tezi, Çankaya Üniversitesi).
  • Şahin A. (2007). Görüntü Steganografide Kullanılan Yeni Metodlar ve Bu Metodların Güvenilirlikleri. (Doktora Tezi, Selçuk Üniversitesi).

İdeal Steganografi Senaryosu: Taşıyıcı Resimlerin Kapasitelerinin Hesaplanması, Frekans Tabanlı Steganografide OPA Yöntemi

Year 2018, , 12 - 21, 26.06.2018
https://doi.org/10.30801/acin.358076

Abstract

Bu çalışmada, steganografi’nin bir dalı olan dijital
resim steganografisinden ve onun bir alt dalı olan frekans tabanlı steganografi
yöntemlerinden öne çıkan ikisi DCT (Discrete Cosine Transform - Ayrık Kosinüs
Dönüşümü) ve DWT (Discrete Wavelet Transform - Kesikli Dalgacık Dönüşümü)’den
bahsedilmiştir. Steganografik yöntemlerin performans hesaplama parametreleri
olan MSE (Mean Squared Error, Ortalama Hata Kare), PSNR (Peak Signal Noise
Ratio - Doruk Sinyal Gürültü Oranı) gibi yöntemler açıklanmış ve bu
parametrelerin değerlerinin arttırılması için resim kapasitesi hesaplama
yöntemleri olan KL-Divergence, JS-Divergence ve QTS (Quard Tree Segmentation - Dörtlü
Ağaç Segmentasyonu)’den bahsedilmiştir. Sonuç olarak resimlerdeki var olan
kapasitenin daha da arttırılmasını sağlayan OPAP (Optimum Pixel Adjustment
Process) yönteminden bahsedilmiş ve geliştirlmiş olan ideal bir steganografi
senaryosundan bahsedilmiştir. Burada, DWT’nin alçak frekanslı ve veri gizlemeye
müsait bandları çıkarma özelliği ve bu bandlarda DCT’nin öznitelik
katsayılarını elde ederek LSB (Least significant bit – En Öznemsiz Bit)
yöntemini uygulamasından faydalanılmıştır. Çalışmamızda ek olarak bu senaryonun
denemesi gerçekleştirilmiş ve sonuç olarak QTS’e göre daha yüksek veri gizleme
kapasitesi olan resimlerin daha yüksek PSNR değerleri verdiği sonucuna ulaşılmıştır.

References

  • Holub, V., Fridrich, J., Denemark, T. (2014). Universal distortion function for steganography in an arbitrary domain, EURASIP Journal on Information Security, 2014(1), s.11-19.
  • Sajedi, H. (2016). Steganalysis based on steganography pattern discovery. Journal of Information Security and Applications, 30, 3-14.
  • Yaghmaee, F., Jamzad M.(2010). Estimating watermarking capacity in gray scale ımages based on ımage complexity , EURASIP Journal on Advances in Signal Processing, ss. 20102010:851920, doi: 10.1155/2010/851920.
  • Subhedar, M.S., Mankar, V.H. (2014). Current status and key issues in image steganography: A survey, Computer Science Review, 13, ss. 95-113.
  • Challita, K., Farhat, H. (2011). Combining steganography and cryptography: new directions. International Journal on New Computer Architectures and Their Applications, 1(1), ss.199-208.
  • Verma, N.(2011). Review of steganography techniques, International Conference and Workshop on Emerging Trends in Technology (ICWET 2011)–TCET, Mumbai, India
  • Zeki, A.M., Ibrahim, A.A., Manaf, A.A.(2012). Steganographic software:analysis and implementation, International Journal Of Computers And Communications, 6(1).
  • Hemalatha, S., Acharya U. D., Renuka, A., Kamath, P.R.(2012). A Novel color image steganography using discrete wavelet transform, CCSEIT-12, October 26-28, 2012, Coimbatore, India.
  • Suvarna P., Chandel, G.S.(2013). Performance analysis of steganography based on 5-wavelet families by 4 levels -dwt suvarna, International Journal of Advance Research in Computer Science and Management Studies, 1(7), ss. 20-33.
  • Dhawale, C. A., Hegadi, R., Jambhekar, N.D.(2014). Performance analysis of digital ımage steganographic algorithm. ICTCS '14, Kasım 14 – 16, 2014, Udaipur, Rajasthan, India, ACM 978-1-4503-3216-3/14/11.
  • Sujatha, P., Purushothaman, S., Rajeswari, R. (2014). Performance study of combined artificial neural network algorithms for ımage steganalysis, In Proceedings of International Conference on Internet Computing and Information Communications, ss. 441-451, Springer India.
  • Liu, Y., Liu, Y., Wu, S., Zhong, S. (2015). What Makes the Stego Image Undetectable? ICIMCS ’15, Ağustos 19-21, 2015, Zhangjiajie, Hunan, China, ACM. ISBN 978-1-4503-3528-7/15/08.
  • Hemalatha, S., Acharya, U.D., Renuka, A.(2015). Wavelet transform based steganography technique to hide audio signals in image, Procedia Computer Science, 47, ss.272-281.
  • Provos, N., Honeyman, P. (2001). Detecting steganographic content on the internet, Center for Information Technology Integration, NDSS 2002, San Diego.
  • Haşiloğlu, A. (2001). Dalgacık dönüşümü ve yapay sinir ağları ile döndürmeye duyarsız doku analizi ve sınıflandırma, Turk J. Engin Environ Sci, 25, ss.405-413.
  • Dalvi, A., Kamathe, R.S. (2015). Color ımage steganography by using dual wavelet transform (DWT SWT). International Journal of Scientific Engineering and Research (IJSER), 3(7), ss.25-41.
  • Bera, S., Dewangan, U., Sharma, M. (2013). Development and analysis of stego ımage using discrete wavelet transform, International Journal of Science and Research (IJSR), India Online ISSN: 2319-7064.
  • Cheddad A., J. Condell, K., Kevitt, P.(2010). Digital ımage steganography: survey and analysis of current methods, Signal Processing, 90(3), ss.727-752.
  • Peterson, A.K. (2005). Introduction to Basic Measures of a Digital Image for Pictorial Collections, Prints & Photographs Division, Library of Congress, Washington, DC, ss. 20540-4720.
  • Muhsin, Z. F., Rehman, A., Altameem, A., Saba, T., & Uddin, M. (2014). Improved quadtree image segmentation approach to region information. The Imaging Science Journal, 62(1), ss. 56-62.
  • Lin,Y-C, Li, T-S (2011). Reversible image data hiding using quad-tree segmentation and histogram shifting, Journal of Multimedia, 6 (4), ss. 349-358.
  • Kaur, S., Goel, N. (2015). Segmentation and block based image steganography using optimal pixel adjustment process and identical approach, 2nd International Conference on Recent Advances in Engineering & Computational Sciences (RAECS), Chandigarh, 2015, ss. 1-5.
  • Nithya , R. K., Nehru, C.P., Ubramanıam, T.B.(2014). Optimal pixel adjustment based reversible steganography, (IJITR) International Journal Of Innovatıve Technology And Research, 2 (3), 2014, ss. 963–966.
  • Demirci, B. (2016). Görüntü steganografi metotları ve performanslarının karşılaştırılması (Doktora Tezi, Selçuk Üniversitesi Fen Bilimleri Enstitüsü).
  • Kaya, H. V. (2015). Watermarking in medical images by using DWT, DCT, DFT and lSB algorithms (Doktora Tezi, Çankaya Üniversitesi).
  • Şahin A. (2007). Görüntü Steganografide Kullanılan Yeni Metodlar ve Bu Metodların Güvenilirlikleri. (Doktora Tezi, Selçuk Üniversitesi).
There are 26 citations in total.

Details

Primary Language Turkish
Journal Section Makaleler
Authors

Ferdi Sönmez

Faruk Takaoğlu This is me

Oğuz Kaynar

Publication Date June 26, 2018
Submission Date November 26, 2017
Published in Issue Year 2018

Cite

APA Sönmez, F., Takaoğlu, F., & Kaynar, O. (2018). İdeal Steganografi Senaryosu: Taşıyıcı Resimlerin Kapasitelerinin Hesaplanması, Frekans Tabanlı Steganografide OPA Yöntemi. Acta Infologica, 2(1), 12-21. https://doi.org/10.30801/acin.358076
AMA Sönmez F, Takaoğlu F, Kaynar O. İdeal Steganografi Senaryosu: Taşıyıcı Resimlerin Kapasitelerinin Hesaplanması, Frekans Tabanlı Steganografide OPA Yöntemi. ACIN. June 2018;2(1):12-21. doi:10.30801/acin.358076
Chicago Sönmez, Ferdi, Faruk Takaoğlu, and Oğuz Kaynar. “İdeal Steganografi Senaryosu: Taşıyıcı Resimlerin Kapasitelerinin Hesaplanması, Frekans Tabanlı Steganografide OPA Yöntemi”. Acta Infologica 2, no. 1 (June 2018): 12-21. https://doi.org/10.30801/acin.358076.
EndNote Sönmez F, Takaoğlu F, Kaynar O (June 1, 2018) İdeal Steganografi Senaryosu: Taşıyıcı Resimlerin Kapasitelerinin Hesaplanması, Frekans Tabanlı Steganografide OPA Yöntemi. Acta Infologica 2 1 12–21.
IEEE F. Sönmez, F. Takaoğlu, and O. Kaynar, “İdeal Steganografi Senaryosu: Taşıyıcı Resimlerin Kapasitelerinin Hesaplanması, Frekans Tabanlı Steganografide OPA Yöntemi”, ACIN, vol. 2, no. 1, pp. 12–21, 2018, doi: 10.30801/acin.358076.
ISNAD Sönmez, Ferdi et al. “İdeal Steganografi Senaryosu: Taşıyıcı Resimlerin Kapasitelerinin Hesaplanması, Frekans Tabanlı Steganografide OPA Yöntemi”. Acta Infologica 2/1 (June 2018), 12-21. https://doi.org/10.30801/acin.358076.
JAMA Sönmez F, Takaoğlu F, Kaynar O. İdeal Steganografi Senaryosu: Taşıyıcı Resimlerin Kapasitelerinin Hesaplanması, Frekans Tabanlı Steganografide OPA Yöntemi. ACIN. 2018;2:12–21.
MLA Sönmez, Ferdi et al. “İdeal Steganografi Senaryosu: Taşıyıcı Resimlerin Kapasitelerinin Hesaplanması, Frekans Tabanlı Steganografide OPA Yöntemi”. Acta Infologica, vol. 2, no. 1, 2018, pp. 12-21, doi:10.30801/acin.358076.
Vancouver Sönmez F, Takaoğlu F, Kaynar O. İdeal Steganografi Senaryosu: Taşıyıcı Resimlerin Kapasitelerinin Hesaplanması, Frekans Tabanlı Steganografide OPA Yöntemi. ACIN. 2018;2(1):12-21.