Robust Steganography Technique for Embedding Secret Images

Authors

  • Nehayat Ezzaldeen Majeed Department of Applied Computer, College of Applied and Medical Sciences, Charmo University, Chamchamal, Kurdistan Region, Iraq
  • Haval Mohammed Sidqi Department of Information Technology, College of Informatics, Sulaimani Polytechnic University, Sulaymaniyah, Kurdistan Region, Iraq

DOI:

https://doi.org/10.32410/huj-10443

Keywords:

Integer wavelet transform (IWT), LSB Steganography, Peak Signal-to-Noise Rate (PSNR), Cover image, Mean Squared Error (MSE)

Abstract

Steganography is a technique used to disguise the existence of a secret communication. It is used in many fields to solve information security problems. Steganography is a technique to embed secret data in a carrier image and obtain a new image that can't actually be distinguished from the original image. This paper proposes steganography method based on least significant bit (LSB) replacement and integer wavelet transform IWT through lifting scheme to achieve high quality of stego image. we will do some pre-processing on the secret image before embedding process. IWT transforms the secret image from spatial domain to a frequency domain and will be divided it into a group of sub-bands, some of which we will use for their utmost importance and ignore some of them.

We have embedded the secret image in a sequential LSB method and in a randomly LSB method and also by the method LSB matching. But after applying our proposed method to the secret image and then embedded it in each of the three above-mentioned methods, it was found that it had a higher degree of imperceptibly and obtained a higher rate of PSNR and the possibility of recovering the secret image without errors. By using the randomly and LSBM methods gives a higher security and resistance to extraction by attackers.

References

A., I. A.-s. (2007). Hiding Data Using LSB-3. J.Basrah Res.

Abdul-Sada, A. I. (2007). Hiding Data Using LSB-3. J.Basrah Res.

Ahmad, M. A., Elloumi, M., Samak, A. H., Al-Sharafi, A. M., Alqazzaz, A., Kaid, M. A., & Iliopoulos, C. (2022). Hiding patients’ medical reports using an enhanced wavelet steganography algorithm in DICOM images. alexandria eng. J., 10577-10592.

Aura, T. (1996). Practical Invisibility in Digital Communication. Information Hiding, 266-278.

Chan, C.-K., & Cheng, L. M. (2004). Hiding data in images by simple LSB substitution. Pattern Recognition, 469-474.

Chen, X., Zou, M., Yang, B., Wang, Z., Wu, N., & Qi, L. (2021). A visually secure image encryption method based on integer wavelet transform and rhombus prediction. Mathematical Biosciences and Engineering/ MBE, 1722–1739.

Gutub, A., & Al-Shaarani, F. (2020). Efficient Implementation of Multi-image Secret Hiding Based on LSB and DWT Steganography Comparisons. Arab. J. Sci. Eng.

Hempstalk, K. (2006). Hiding Behind corners Using edges in images for better steganography. Multimed. Tools Appl.

Honeyman, N. P. (2003). Hide and seek: An introduction to steganography. IEEE.

Kaur, H., & Rani, J. (2016). A Survey on different techniques of steganography. MATIC Web of conference.

Ker, A. D. (2004). Improved Detection of LSB Steganography in Grayscale Images. Lect. Notes Comput. Sci., 97-115.

Maiti, S., Nayak, M. R., & Sarkar, S. K. (2017). Modified Least Significant Bit ( LSB ) Matching Technique for Robust Information Hiding. J. Emerg. Technol. Innov. Res., 193-200.

Mielikainen, J. (2006). LSB matching revisited. IEEE Signal Process. Lett., 285-287.

Miri, A., & Faez, K. (2018). An image steganography method based on integer wavelet transform,” Multimed. Tools Appl., vol. 77, no. 11, pp. Multimed Tools Appl., 13133-13144.

Petitcolas, F. A., Anderson, R. J., & Kuhn, M. G. (1999). Information hiding - a survey. IEEE, 1062-1078.

Pratik , D Shah ; R, S Bichkar. (2018). P. A secure spatial domain image steganography using genetic algorithm and linear congruential generator. Springer Nature Singapore Pte Ltd. 2018. International Conference on Intelligent Computing.

Provos, N., & Honeyman, P. (2003). Hide and seek: An introduction to steganography. IEEE Secur, 32-44.

S, M., M, R. N., & S, K. S. (2017). Modified Least Significant Bit ( LSB ) Matching Technique for Robust Information Hiding. J. Emerg. Technol. Innov.

Sahu, A. K., & Swain, G. (2019). A Novel n-Rightmost Bit Replacement Image Steganography Technique. 3DR EXPRESS.

Setiadi, D. I. (2021). PSNR vs SSIM: imperceptibility quality assessment for image steganography. Multimed. Tools Appl.

Shah, P. D., & Bichkar, R. S. (2018). A secure spatial domain image steganography using genetic algorithm and linear congruential generator. International Conference on Intelligent Computing, (pp. 119-129).

Subhedar, M. S., & Mankar, V. H. (2019). Secure image steganography using framelet transform and bidiagonal SVD. Springer Science.

Wang, Y., Tang, M., & Wang, Z. (2020). High-capacity adaptive steganography based on LSB and Hamming code. Optik (Stuttg). .

Weber, A. G. (2018). Ming Hsieh Department of Electrical Engineering USC-SIPI Report # 432 The USC-SIPI Image Database : Version 6 Accessing the Database Images Database on CD-R Media,.

Zhu, L., Song, H., Zhang, X., Yan, M., Zhang, T., Wang, X., & Xu, J. (2020). A robust meaningful image encryption scheme based on block compressive sensing and SVD embedding,” Signal Proc107629, 2020, doi: 10.1016/j.sigpro.2020. Signal Processing.

Published

2022-12-30

How to Cite

Majeed, N. E., & Sidqi, H. M. (2022). Robust Steganography Technique for Embedding Secret Images: . Halabja University Journal, 7(4), 264-281. https://doi.org/10.32410/huj-10443

Similar Articles

1-10 of 36

You may also start an advanced similarity search for this article.