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An efficient and robust watermarking approach based on single value decompression, multi-level DWT, and wavelet fusion with scrambled medical images

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Abstract

This paper offers a medical image watermarking approach based on Wavelet Fusion (WF), Singular Value Decomposition (SVD), and Multi-Level Discrete Wavelet Transform (M-DWT) with scrambling techniques for securing the watermarks images. The proposed approach can be used for providing multi-level security in various applications such as military, copyright protection, and telemedicine systems. The key idea of the projected approach is to first combine two digital watermark images into a single fused watermark to increase the embedded information payload. Then, the fused watermark is scrambled using Arnold and Chaotic algorithms. Finally, the scrambled fused watermark is embedded in the cover image using the SVD and three-level DWT algorithms. The selection of the Arnold and chaotic for watermark encryption is attributed to confirm robustness which resists several types of multimedia attacks and upturn the security level. This paper also presents a comparative study of the proposed approach for different digital images to determine its robustness and stability. Several simulation results reveal that the proposed system improves the capacity and security of embedded medical watermarks without affecting the cover image quality. In conclusion, the proposed approach achieved not only precise acceptable perceptual quality with admired Peak Signal-to-Noise Ratio (PSNR) values but similarly high Correlation Coefficient (Cr) and SSIM values in the existence of severe attacks.

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References

  1. Al-Afandy KA et al (2018) Robust hybrid watermarking techniques for different color imaging systems. Multimed Tools Appl 77(19):25709–25759

    Article  Google Scholar 

  2. Ali M, Ahn CW, Siarry P (2014) Differential evolution algorithm for the selection of optimal scaling factors in image watermarking. Eng Appl Artif Intell 31:15–26

    Article  Google Scholar 

  3. Alshanbari, Hanan S. (2020). “Medical image watermarking for ownership & tamper detection.” Multimed Tools Appl : 1–16

  4. Atlam, Hany F., et al. (2020). “Internet of Things Forensics: A Review.” Internet of Things : 100220

  5. Dhanalakshmi, R, and K Thaiyalnayaki (2010). “Dual watermarking scheme with encryption.” arXiv preprint arXiv:1002.2414

  6. Dhar, Pranab Kumar, Rakib Hasan, and Tetsuya Shimamura (2018). “Color Image Watermarking Based on Radon Transform and Jordan Decomposition.” Digital Image and Video Watermarking and Steganography. IntechOpen

  7. Elashry IF et al (2009) Homomorphic image encryption. Journal of Electronic Imaging 18(3):033002

    Article  Google Scholar 

  8. Emad El-Din, Aml, Ezz El-Din Hemdan, and Ayman El-Sayed (2019). “Malicious Website Detection using Machine Learning on Apache Spark.” Menoufia Journal of Electronic Engineering Research 28.ICEEM2019-Special Issue : 337–342

  9. El-Din, Hemdan Ezz, and DH Manjaiah (2017). “Internet of things in cloud computing.” Internet of Things: Novel advances and envisioned applications. Springer, Cham. 299–311

  10. El-Din, Hemdan Ezz, and DH Manjaiah (2017). “Internet of nano things and industrial internet of things.” Internet of Things: Novel advances and envisioned applications. Springer, Cham. 109–123

  11. Abd El-Naby, Aya, Ezz El-din Hemdan, and Ayman EL-SAYED (2019). “An Efficient Credit Card Fraud Detection Model.” Menoufia Journal of Electronic Engineering Research 28.ICEEM2019-Special Issue : 332–336

  12. El-Refaey, Amir E., et al. (2019). “Triple C: A New Algorithm for ECG Cancelable Biometric System.” Menoufia Journal of Electronic Engineering Research 28.ICEEM2019-Special Issue : 43–50

  13. Ganic E, Eskicioglu AM (2005) Robust embedding of visual watermarks using discrete wavelet transform and singular value decomposition. Journal of electronic imaging 14(4):043004

    Article  Google Scholar 

  14. Giakoumaki A, Pavlopoulos S, Koutsouris D (2006) Secure and efficient health data management through multiple watermarking on medical images. Med Biol Eng Comput 44(8):619–631

    Article  Google Scholar 

  15. Harish NJ, Kumar BBS, Kusagur A (2013) Hybrid robust watermarking techniques based on DWT, DCT, and SVD. International Journal of Advanced Electrical and electronics engineering 2(5):137–143

    Google Scholar 

  16. Hemdan, Ezz El-Din, and DH Manjaiah (2017). “Internet of Nano-Things Forensics: Performing Digital Forensics in Nanoscale Systems.” Internet of Things (IoT). CRC Press. 143–162

  17. Hemdan, Ezz El-Din, and DH Manjaiah (2018). “Cybercrimes investigation and intrusion detection in internet of things based on data science methods.” Cognitive Computing for Big Data Systems Over IoT. Springer, Cham. 39–62

  18. Hemdan, Ezz El-Din, and DH Manjaiah (2020). “Digital Investigation of Cybercrimes Based on Big Data Analytics Using Deep Learning.” Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications. IGI Global. 615–632

  19. Hemdan, Ezz El-Din, et al. (2013). “C11. Hybrid Digital Image Watermarking Technique for Data Hiding.” 2013 30th National Radio Science Conference (NRSC). IEEE

  20. Hemdan, EED, et al. (2013). “An efficient image watermarking approach based on wavelet fusion and singular value decomposition in wavelet domain.” Proceeding of 3rd International Conference on Advanced Control Circuits And Systems (ACCS’013). No. 1–10

  21. Jindal, Himanshu, Singara Singh Kasana, and Sharad Saxena (2016). “A Novel Image Zooming Technique Using Wavelet Coefficients.” Proceedings of the International Conference on Recent Cognizance in Wireless Communication & Image Processing. Springer, New Delhi

  22. Kannamma A, Pavithra K, Subha Rani S (2012) Double watermarking of DICOM medical images using wavelet decomposition technique. Eur J Sci Res 70(1):46–55

    Google Scholar 

  23. Kaur S, Jindal H (2017) Enhanced image watermarking technique using wavelets and interpolation. International Journal of Image, Graphics and Signal Processing 11.7:23

    Article  Google Scholar 

  24. Khare, Priyank, and Vinay Kumar Srivastava (2020). “A secured and robust medical image watermarking approach for protecting integrity of medical images.” Trans Emerg Telecommun Technol

  25. Lagzian, Samira, Mohsen Soryani, and Mahmood Fathy (2011). “Robust watermarking scheme based on RDWT-SVD: Embedding Data in All subbands.” 2011 International Symposium on Artificial Intelligence and Signal Processing (AISP). IEEE

  26. Lai C-C, Tsai C-C (2010) Digital image watermarking using discrete wavelet transform and singular value decomposition. IEEE Trans Instrum Meas 59(11):3060–3063

    Article  Google Scholar 

  27. Langelaar GC, Setyawan I, Lagendijk RL (2000) Watermarking digital image and video data. A state-of-the-art overview. IEEE Signal Process Mag 17(5):20–46

    Article  Google Scholar 

  28. Leng, Lu, Ming Li, and Andrew Beng Jin Teoh (2013). “Conjugate 2DPalmHash code for secure palm-print-vein verification.” 2013 6th International Congress on Image and Signal Processing (CISP). Vol. 3. IEEE

  29. Leng L, Teoh ABJ (2015) Alignment-free row-co-occurrence cancelable palmprint fuzzy vault. Pattern Recogn 48(7):2290–2303

    Article  Google Scholar 

  30. Leng, Lu, et al. (2010). “Dynamic weighted discrimination power analysis in DCT domain for face and palmprint recognition.” 2010 international conference on information and communication technology convergence (ICTC). IEEE

  31. Leng L et al (2014) Analysis of correlation of 2DPalmHash code and orientation range suitable for transposition. Neurocomputing 131:377–387

    Article  Google Scholar 

  32. Leng L et al (2014) A remote cancelable palmprint authentication protocol based on multi-directional two-dimensional PalmPhasor-fusion. Security and Communication Networks 7(11):1860–1871

    Article  Google Scholar 

  33. Leng L et al (2015) Orientation range of transposition for vertical correlation suppression of 2DPalmPhasor code. Multimed Tools Appl 74(24):11683–11701

    Article  Google Scholar 

  34. Leng L et al (2017) Dual-source discrimination power analysis for multi-instance contactless palmprint recognition. Multimed Tools Appl 76(1):333–354

    Article  Google Scholar 

  35. Liu R, Tan T (2002) An SVD-based watermarking scheme for protecting rightful ownership. IEEE transactions on multimedia 4(1):121–128

    Article  Google Scholar 

  36. Mahajan LH, Patil SA (2013) Image watermarking scheme using SVD. International Journal of Advance Research in Science and Engineering 2(6):69–77

    Google Scholar 

  37. Makbol NM, Khoo BE (2013) Robust blind image watermarking scheme based on redundant discrete wavelet transform and singular value decomposition. AEU-International Journal of Electronics and Communications 67(2):102–112

    Article  Google Scholar 

  38. Mander K, Jindal H (2017) An improved image compression-decompression technique using block truncation and wavelets. International Journal of Image, Graphics and Signal Processing 9.8:17

    Article  Google Scholar 

  39. Mittal A, Jindal H (2017) Novelty in Image Reconstruction using DWT and CLAHE. International Journal of Image, Graphics and Signal Processing 9.5:28

    Article  Google Scholar 

  40. Potdar, Vidyasagar M., Song Han, and Elizabeth Chang (2005). “A survey of digital image watermarking techniques.” INDIN'05. 2005 3rd IEEE International Conference on Industrial Informatics, 2005. IEEE

  41. Pradhan C, Rath S, Bisoi AK (2012) Non blind digital watermarking technique using DWT and cross chaos. Procedia Technology 6:897–904

    Article  Google Scholar 

  42. Rastegar S, Namazi F, Yaghmaie K, Aliabadian A (2011) Hybrid watermarking algorithm based on singular value decomposition and radon transform. AEU-International Journal of Electronics and Communications 65(7):658–663

    Article  Google Scholar 

  43. I Selim, Gamal Eldin, et al. (2019). “Anomaly Activities Detection System in Critical Water SCADA Infrastructure Using Machine Learning Techniques.” Menoufia Journal of Electronic Engineering Research 28.ICEEM2019-Special Issue : 343–384

  44. Shieh J-M, Lou D-C, Chang M-C (2006) A semi-blind digital watermarking scheme based on singular value decomposition. Computer Standards & Interfaces 28(4):428–440

    Article  Google Scholar 

  45. Singh, Vipula (2011). “Digital watermarking: A tutorial.” Cyber Journals, Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), January Edition

  46. Singh D, Singh SK (2017) DWT-SVD and DCT based robust and blind watermarking scheme for copyright protection. Multimed Tools Appl 76(11):13001–13024

    Article  Google Scholar 

  47. Srivastava A, Saxena P (2013) DWT-DCT-SVD based semiblind image watermarking using middle frequency band. IOSR J Comput Eng 12(2):63–66

    Article  Google Scholar 

  48. Thakkar FN, Srivastava VK (2017) A blind medical image watermarking: DWT-SVD based robust and secure approach for telemedicine applications. Multimed Tools Appl 76(3):3669–3697

    Article  Google Scholar 

  49. Wang, Qiang, et al. (2008). “Digital image encryption research based on dwt and chaos.” 2008 Fourth International Conference on Natural Computation. Vol. 5. IEEE

  50. Zear A, Singh AK, Kumar P (2018) A proposed secure multiple watermarking technique based on DWT, DCT and SVD for application in medicine. Multimed Tools Appl 77(4):4863–4882

    Article  Google Scholar 

  51. Zhang L et al (2011) FSIM: a feature similarity index for image quality assessment. IEEE Trans Image Process 20(8):2378–2386

    Article  MathSciNet  Google Scholar 

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Hemdan, E.ED. An efficient and robust watermarking approach based on single value decompression, multi-level DWT, and wavelet fusion with scrambled medical images. Multimed Tools Appl 80, 1749–1777 (2021). https://doi.org/10.1007/s11042-020-09769-7

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  • DOI: https://doi.org/10.1007/s11042-020-09769-7

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