Volume 10 , Issue 1 , PP: 89-99, 2023 | Cite this article as | XML | Html | PDF | Full Length Article
Mohamed Saber 1 * , El-Sayed M. El-Kenawy 2 , Abdelhameed Ibrahim 3 , Marwa M. Eid 4
Doi: https://doi.org/10.54216/FPA.100105
One of the main methods used to provide security for medical records when exchanging these records through open networks is digital watermarking. In order to preserve the privacy of patients, this system also requires a means to secure images. In this paper, a watermarking based on discrete wavelet transform (DWT), and discrete and discrete cosine transform (DCT) in cascade provides more robustness and security. DCT divides the image into low and high-frequency regions, watermarking message can be embedded into low-frequency regions to prevent distortion of the original image. DWT splits the image into four frequency coefficients; horizontal, vertical, approximation, and detailed frequency component. The judgment factors for the strength of the watermark system are robustness, invisibility, and embedded message capacity. Invisibility means transparency of the watermark logo or data in the original or host image without any distortion. Capacity data payload means the size of the embedded image which is related to the amount of data or logo size that will be embedded in the host image. Robustness refers to the capability of the watermark to stand with the host image operations. In this paper, we propose an optimizer to trade-off between robustness, invisibility, and message capacity. Three metrics were employed to assess the results achieved by the proposed approach, namely, Peak Signal-to-Noise Ratio (PSNR), Normalized Cross Correlation (NCC), and Image Fidelity (IF). The achieved results confirmed the effectiveness and superiority of the proposed approach for real-world digital watermarking applications.
Digital watermarking , Optimization , Information hiding , Digital security
[1] Mathivanan P, Balaji Ganesh A, QR code-based color image cryptography for the secured transmission of ECG signal. Multimed Tools Appl, 78(6), 6763–6786, 2019.
[2] Anand A, Singh AK, Lv Z, Bhatnagar G, Compression-then encryption based secure watermarking technique for the smart healthcare system. IEEE Multimedia, 27(4),133–134, 2020.
[3] Abuadbba A, Member S, Khalil I, Member S, Walsh-hadamard based 3D steganography for protecting sensitive information in point-of-care. IEEE Trans Biomed Eng., 9294(2), 1–10, 2016.
[4] Anand A, Singh, An improved DWT-SVD domain watermarking for medical information security. Computer Communication, 152, 72-80, 2020.
[5] Banerjee S, Singh GK, A new approach of ECG steganography and prediction using deep learning. Biomed Signal Process Control, 64, 2020.
[6] Ibrahim, Abdelhameed, Seyedali Mirjalili, Mohammed El-Said, Sherif SM Ghoneim, Mosleh M. Al-Harthi, Tarek F. Ibrahim, and El-Sayed M. El-Kenawy. "Wind speed ensemble forecasting based on deep learning using adaptive dynamic optimization algorithm." IEEE Access 9 (2021): 125787-125804.
[7] Mathivanan P, Balaji Ganesh A , ECG steganography based on tunable Q-factor wavelet transform and singular value decomposition. Int J Imaging Syst Technol, 31(1), 270–287, 2021.
[8] Almeida BDA, Doneda D, Ichihara MY, Barral-Netto M, et. Al., Personal data usage and privacy considerations in the COVID-19 global pandemic. Cien Saude Colet, 25, 2487–2492, 2020.
[9] Bose B, Dey D, Sengupta A, Mulchandani N, A novel medical image encryption using cyclic coding in covid-19 pandemic situation. J Phys Conf Ser Pap, 1797, 1–7, 2021.
[10] Reyad O, Karar ME, Secure CT—image encryption for COVID - 19 infections using HBBS— based multiple key—streams. Arab J Sci Eng., 46(4), 3581–3593, 2021.
[11] Sanivarapu PV, Rajesh KNVPS, Reddy NVR, Reddy NCS, Patient data hiding into ECG signal using watermarking in transform domain. Australas Phys Eng Sci Med., 43, 213-226, 2020.
[12] Anand A, Singh AK, Watermarking techniques for medical data authentication: a survey. Multimed Tools Appl., 80(20), 30165-30197, 2021.
[13] Agarwal C, Mishra A, Sharma A, Bedi P, Optimized gray-scale image watermarking using DWT-SVD and firefly algorithm. Expert Syst Appl 41(17), 7858–7867, 2014.
[14] Alotaibi SS, Optimization insisted watermarking model: hybrid firefly and Jaya algorithm for video copyright protection. Soft Comput., 24(19), 14809–14823, 2020.
[15] Edward Jero S, Ramu P, Swaminathan R, Imperceptibility robustness tradeoff studies for ECG steganography using continuous ant colony optimization. Expert Syst. Appl., 49, 123-135, 2016.
[16] El-Kenawy, El-Sayed M., Marwa Eid, and Alshimaa H. Ismail. "A New Model for Measuring Customer Utility Trust in Online Auctions." International Journal of Computer Applications 975: 8887.
[17] Alexander Savelyev, Copyright in The Blockchain ERA: Promises and Challenges. Computer law & security review, 34(3), 550-561, 2018.
[18] Shigeru Fujimura, Hiroki Watanabe, et. al ,BRIGHY: A Concept for a Decentralized Rights Management System Based on Blockchain. IEEE 5th International Conference on Consumer Electronics Berlin (ICCE-Berlin), 345-346, 2015.
[19] Ruzhi Xu, Lu Zhang, Huawei Zhao and Yun Peng,, Design of Network Media’s Digital Rights Management Scheme Based on Blockchain Technology. IEEE 13th International Symposium on Autonomous Decentralized Systems, 128-133, 2017.
[20] L. P. Feng, L. B. Zheng, P. Cao, ―A DWT-DCT based blind watermarking algorithm for copyright protection. Proceedings of 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT), Chengdu, China, 455–458, 2010.
[21] Sharma A, Singh AK, Ghrera SP. Secure hybrid robust watermarking technique for medical images. Procedia Computer Science, 70, 778-784, 2015.
[22] Al-maweri NAAS, Adnan WAW, Rahman Ramli A, Samsudin K, Ahmad SMS, A hybrid digital image watermarking algorithm based on DCT-DWT and auto thresholding. Security Comm. Networks, 8(18), 4373 4395, 2015.
[23] Hu H-T, Hsu L-Y., Collective blind image watermarking in DWT-DCT domain with adaptive embedding strength governed by quality metrics. Multimedia Tools Appl., 76(5), 6575-6594, 2017.
[24] S. Natu, P. Natu, and T. Sarode, Improved robust digital image watermarking with SVD and hybrid transform. Proceedings of the International Conference on Intelligent Communication and Computational Techniques (ICCT), Jaipur, India, 177–181, 2017.
[25] T. K. Al-Shayea, J. M. Batalla, C. X. Mavromoustakis, G. Mastorakis, Embedded dynamic modification for efficient watermarking using different medical inputs in IoT. IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Limassol, Cyprus, 1-6, 2019.
[26] Sharma V, Mir RN., An enhanced time efficient technique for image watermarking using ant colony optimization and light gradient boosting algorithm, J. King Saud Univ–Computer Inform Sci., 34(3), 645-626, 2022.
[27] El-kenawy, El-Sayed M., Hattan F. Abutarboush, Ali Wagdy Mohamed, and Abdelhameed Ibrahim. "Advance artificial intelligence technique for designing double T-shaped monopole antenna." CMC-COMPUTERS MATERIALS & CONTINUA 69, no. 3 (2021): 2983-2995.
[28] Zhong X,Huang P-C, Mastorakis S, Shih FY., An automated and robust image watermarking scheme based on deep neural networks. IEEE Trans Multimedia, 23, 1951-1961, 2020.
[29] N. Yadav, D. Rajpoot, S. K. Dhakad, Optimization of watermarking in image by using particle swarm optimization algorithm. 6th International Conference on Signal Processing and Communication (ICSC), Noida, India, 85-90, 2020.
[30] Rajani D, Rajesh Kumar P., An optimized blind watermarking scheme based on principal component analysis in redundant discrete wavelet domain. Signal Process., 172, 2020.
[31] Lee J, Seo Y, Kim D., Convolutional neural network-based digital image watermarking adaptive to the resolution of image and watermark. Appl Sci., 10(6854),1-20, 2020.
[32] Frattolillo F, A watermarking protocol based on Blockchain. Appl Sci.,10(7746):1-18, 2020.
[33] Kazemi M, Pourmina MA, Mazinan AH., Analysis of watermarking framework for color image through a neural network-based approach. Complex Intell. Syst., 6, 213-220, 2020.
[34] Garg P, Kishore RR., Optimized color image watermarking through watermark strength optimization using particle swarm optimization technique. J Inform Optim Sci., 41(6):1499- 1512, 2020.
[35] R. S. Kavitha,U. Eranna,M.N.Giriprasad, DCT-DWT based digital watermarking and extraction using neural networks. International Conference on Artificial Intelligence and Signal Processing (AISP), Amaravati, India, 1-5, 2020.
[36] Song M, Wang H, Wu J, Yan X, Yuan L, Tu Y. , A robust watermarking hybrid algorithm for color image. MATEC Web Conf., 336(07012), 1-9, 2021.
[37] Begum M, Uddin MS., Multiple image watermarking with discrete cosine transform. J Computer Comm., 9, 88-94, 2021.
[38] O. Evsutin and Y. Meshcheryakov, The use of the blockchain technology and digital watermarking to provide data authenticity on a mining enterprise. Sensors, 20 (12), 1–20, 2020.
[39] Z. Ma, M. Jiang, H. Gao and Z. Wang, Blockchain for digital rights management. Future Generation Computer Systems, 89(1), 746–764, 2018.
[40] El-kenawy, El-Sayed M., Marwa M. Eid, and Abdelhameed Ibrahim. "Anemia estimation for covid-19 patients using a machine learning model." Journal of Computer Science and Information Systems 17, no. 11 (2021): 2535-1451.
[41] M. L. P. Gort, C. Feregrino-Uribe, A. Cortesi and F. Fernndez-Pena, Hqr-scheme: A high quality and resilient virtual primary key generation approach for watermarking relational data. Expert Systems with Applications, 138(1), 1–28, 2019.
[42] K. Rani and C. Sharma, Tampering detection of distributed databases using blockchain technology. Twelfth Int. Conf. on Contemporary Computing (IC3), Noida, India, 1–4, 2019.
[43] S. Sahoo, R. Roshan, V. Singh and R. Halder, Bdmark: A blockchain driven approach to big data watermarking. Asian Conf. on Intelligent Information and Database Systems, Phuket, Thailand, Springer, 71–84, 2020.
[44] H. Nasser AlEisa, E. M. El-kenawy, A. Ali Alhussan, M. Saber, A. A. Abdelhamid et al., Transfer learning for chest x-rays diagnosis using dipper throated algorithm, Computers. Materials & Continua, 73(2), 2371–2387, 2022.
[45] Mohamed Saber, Efficient Phase Recovery System. Indonesian Journal of Electrical Engineering and Computer Science, 5 (1), 123-129, 2017.
[46] Mohamed Saber, A novel design and Implementation of FBMC transceiver for low power applications. Indonesian Journal of Electrical Engineering and Informatics, 8(1), 83-93, 2020.