Multilevel Text Protection System Using AES and DWT-DCT-SVD Techniques
Article Sidebar
Main Article Content
Abstract
In the digital age, protecting intellectual property and sensitive information against unauthorized access is of paramount importance. While encryption helps keep data private and steganography hides the fact that data are present, using both together makes the security much stronger. This paper introduces a new way to hide encrypted text inside color images by integrating discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD), along with AES-GCM encryption, to guarantee data integrity and authenticity. The proposed method operates in the YCbCr color space, targeting the luminance (Y) channel to preserve perceptual quality. Embedding is performed within the HL subband obtained from DWT decomposition via SVD coefficients extracted from DCT-transformed images in the midfrequency band. A content-aware strategy combining Gaussian blurring, Canny edge detection, and zigzag scanning is employed to increase robustness against image processing attacks. The experimental results demonstrate the effectiveness of the proposed approach, which achieves up to a 10.4% improvement in PSNR, an SSIM score of 0.996, and a 0.10% increase in NCC over those of previous methods, which mostly rely on grayscale images. These results reflect the ability of the system to maintain high visual quality while offering strong resilience and security for embedded data in full-color images.
Article Details
Issue
Section
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
References
[1] M. E. Mahdi and N. H. M. Ali, “Copy move image forgery detection using multi-level local binary pattern algorithm,” Journal of Engineering, vol. 30, no. 6, pp. 141–157, 2024, doi: 10.31026/j.eng.2024.06.09.
[2] G. Sumbul, S. Nayak, and B. Demir, “SD-RSIC: Summarization-driven deep remote sensing image captioning,” IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 8, pp. 6922–6934, 2020.
[3] N. M. Khassaf and N. H. M. Ali, “Improving pre-trained CNN-LSTM models for image captioning with hyper-parameter optimization,” Engineering, Technology & Applied Science Research, vol. 14, no. 5, pp. 17337–17343, 2024.
[4] J. H. Lim, C. S. Chan, K. W. Ng, L. Fan, and Q. Yang, “Protect, show, attend and tell: Empowering image captioning models with ownership protection,” Pattern Recognition, vol. 122, p. 108285, 2022.
[5] S. A. Shams, A. M. Abdulkareem, and A. A. Qasim, "Theoretical background of steganography," Mesopotamian Journal of CyberSecurity, vol. 1, no. 1, pp. 1–7, 2021.
[6] Y. Hua, X. Xi, C. Qu, J. Du, M. Weng, and B. Ye, “An adaptive watermarking for remote sensing images based on maximum entropy and discrete wavelet transformation,” KSII Transactions on Internet and Information Systems, vol. 18, no. 1, pp. 192–210, 2024.
[7] M. Begum and M. S. Uddin, “Digital image watermarking techniques: a review,” Information, vol. 11, no. 2, p. 110, 2020, doi: 10.3390/info11020110.
[8] A. Ali, S. Albitar, and F. Chio, "Digital steganography in smart healthcare protects patient privacy by hiding sensitive medical data within non sensitive files to prevent unauthorized people," Mesopotamian Journal of CyberSecurity, vol. 4, no. 2, pp. 20–62, 2024.
[9] T. K. Araghi and D. Megías, “Analysis and effectiveness of deeper levels of SVD on performance of hybrid DWT and SVD watermarking,” Multimedia Tools and Applications, vol. 83, no. 2, pp. 3895–3916, 2024.
[10] S. Solak, A. M. Abdirashid, A. Adjevi, and A. K. Sahu, “Robust data hiding method based on frequency coefficient variance in repetitive compression,” Engineering Science and Technology, an International Journal, vol. 56, p. 101756, 2024.
[11] S. Haimour, M. R. Al-Mousa, and R. R. Marie, “Using chaotic stream cipher to enhance data hiding in digital images,” arXiv preprint arXiv:2101.00897, 2021.
[12] P. Mohan, B. Kuppuraj, and S. Chellai, “An enhanced security measure for multimedia images using hadoop cluster,” International Journal of Operations Research and Information Systems (IJORIS), vol. 12, no. 3, pp. 1–7, 2021.
[13] O. F. A. Wahab, A. A. M. Khalaf, A. I. Hussein, and H. F. A. Hamed, “Hiding data using efficient combination of RSA cryptography, and compression steganography techniques,” IEEE Access, vol. 9, pp. 31805–31815, 2021.
[14] M. Hamidi, M. E. Haziti, H. Cherifi, and M. E. Hassouni, “A hybrid robust image watermarking method based on DWT-DCT and SIFT for copyright protection,” Journal of Imaging, vol. 7, no. 10, p. 218, 2021.
[15] M. A. A. Khader, S. Kavileswarapu, R. Sarkar, and S. Ganapathy, “Secure text in image steganography using pixel-based algorithm.”
[16] F. Horasan et al., “DWT-SVD based watermarking for high-resolution medical holographic images,” Complexity, vol. 2022, no. 1, p. 3154650, 2022.
[17] A. Zear and P. K. Singh, “Secure and robust color image dual watermarking based on LWT-DCT-SVD,” Multimedia Tools and Applications, vol. 81, no. 19, pp. 26721–26738, 2022.
[18] B. Mokashi et al., “Efficient hybrid blind watermarking in DWT-DCT-SVD with dual biometric features for images,” Contrast Media & Molecular Imaging, vol. 2022, no. 1, p. 2918126, 2022.
[19] B. Bharathkumar, S. Logeswar, S. Sudharsun, and B. Karthikeyan, “An enhanced triple prime encryption approach for image encryption in LSB steganography,” in Proc. 2023 First Int. Conf. on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI), pp. 1–6, IEEE, 2023.
[20] M. Takaoğlu, A. Özyavaş, N. Ajlouni, and F. Takaoğlu, “Highly secured hybrid image steganography with an improved key generation and exchange for one-time-pad encryption method,” Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, vol. 23, no. 1, pp. 101–114, 2023.
[21] S. L. Gomez-Coronel, E. Moya-Albor, J. Brieva, and A. Romero-Arellano, "A Robust and Secure Watermarking Approach Based on Hermite Transform and SVD-DCT," Applied Sciences, vol. 13, no. 14, p. 8430, 2023.
[22] S. Rahman, J. Uddin, M. Zakarya, H. Hussain, A. A. Khan, A. Ahmed, and M. Haleem, "A Comprehensive Study of Digital Image Steganographic Techniques," IEEE Access, vol. 11, pp. 6770–6791, 2023.
[23] X. Li, "Advanced Reversible Data Hiding Techniques in JPEG Images: Methods, Applications, and Future Perspectives," Applied and Computational Engineering, vol. 94, pp. 77–85, 2024.
[24] S. Rahman, J. Uddin, H. Hussain, S. Shah, A. Salam, F. Amin, I. de la Torre Díez, D. L. R. Vargas, and J. C. M. Espinosa, "A novel and efficient digital image steganography technique using least significant bit substitution," Scientific Reports, vol. 15, no. 1, p. 107, 2025.
[25] H. A. Ahmed, A. Mahfoud, and O. I. Al-Sanjary, "Comprehensive Review of Cryptography and Steganography Algorithms," Journal of Information Systems Engineering and Management, vol. 10, no. 29s, pp. 211–228, 2025.
[26] M. J. Dworkin, "Recommendation for block cipher modes of operation: Galois/Counter Mode (GCM) and GMAC," 2007.
[27] R. Koju and S. R. Joshi, "Comparative analysis of color image watermarking technique in RGB, YUV, and YCbCr color channels," Nepal Journal of Science and Technology, vol. 15, no. 2, pp. 133–140, 2014.
[28] M. R. PourArian and A. Hanani, "Blind steganography in color images by double wavelet transform and improved Arnold transform," Indonesian Journal of Electrical Engineering and Computer Science, vol. 3, no. 3, pp. 586–600, 2016.
[29] R. Dhar, R. Gupta, and K. L. Baishnab, "An analysis of CANNY and LAPLACIAN of GAUSSIAN image filters in regard to evaluating retinal image," in 2014 International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE), pp. 1–6, IEEE, 2014.
[30] Z. Zurinahni, J. S. Teh, M. Alawida, and A. Alabdulatif, "Hybrid SVD-based image watermarking schemes: a review," IEEE Access, vol. 9, pp. 32931–32968, 2021.
[31] J. Sharma, K. Kumar, P. Jain, R. H. C. Alfilh, and H. Alkattan, "Enhancing intrusion detection systems with adaptive neuro-fuzzy inference systems," Mesopotamian Journal of CyberSecurity, vol. 5, no. 1, pp. 1–10, 2025.
[32] B. Singh and M. K. Sharma, "Watermarking technique for document images using discrete curvelet transform and discrete cosine transform," Multimedia Tools Appl., pp. 1–25, 2024.
[33] A. Tareef, K. Al-Tarawneh, and A. Sleit, "Block-Based Watermarking for Robust Authentication and Integration of GIS Data," Eng. Technol. Appl. Sci. Res., vol. 14, no. 5, pp. 16340–16345, 2024.
[34] M. G. Martini, "Measuring objective image and video quality: On the relationship between SSIM and PSNR for DCT-based compressed images," IEEE Trans. Instrum. Meas., 2025.
[35] S. Boopathiraja, V. Punitha, P. Kalavathi, and V. B. Surya Prasath, "Computational 2D and 3D medical image data compression models," Arch. Comput. Methods Eng., vol. 29, no. 2, pp. 975–1007, 2022.
[36] W. Kim, "A random focusing method with Jensen–Shannon divergence for improving deep neural network performance ensuring architecture consistency," Neural Process. Lett., vol. 56, no. 4, p. 199, 2024.
[37] X. Cao, W. Zhang, Q. Zhou, C. Zhu, and N. Ren, "Template Watermarking Algorithm for Remote Sensing Images Based on Semantic Segmentation and Ellipse-Fitting," Remote Sens., vol. 17, no. 3, p. 502, 2025.
[38] S. S. Rajput, B. Mondal, and F. Q. Warsi, "A robust watermarking scheme via optimization-based image reconstruction technique," Multimedia Tools Appl., vol. 82, no. 16, pp. 25039–25060, 2023.
[39] R. Ramos and B. Martins, "Using neural encoder-decoder models with continuous outputs for remote sensing image captioning," IEEE Access, vol. 10, pp. 24852–24863, 2022.
[40] G. Sumbul, S. Nayak, and B. Demir, "SD-RSIC: Summarization-Driven Deep Remote Sensing Image Captioning," IEEE Trans. Geosci. Remote Sens., vol. 59, no. 8, pp. 6922–6934, 2021.