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A robust and secured adaptive image watermarking using social group optimization

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Abstract

Watermarking is the process of inserting concealed data into carrier data to authenticate the owner of the material. To achieve optimal performance, we present an intelligent system for watermarking that combines a meta-heuristic method with an embedding technique. The suggested work proposes a blind watermarking technique that embeds the watermark bits in the best location of discrete cosine transform blocks while taking advantage of the discrete wavelet transform's features. To safeguard the embedded watermark, a two-step security mechanism is used: first, the column values are shuffled using a proposed shuffling algorithm, and then the scrambled watermark is encrypted using the Arnold encryption scheme. The primary goal of any watermarking technology is to protect embedded data from various attacks while maintaining the carrier data's quality. By tailoring the embedding site for watermark encapsulation, the recommended technique achieves an acceptable balance of these two characteristics known as imperceptibility and resilience. A meta-heuristic algorithm based on human social behavior is employed to optimize the placement. The social group optimization (SGO) algorithm is a new member of the family of meta-heuristic algorithms. No attempt has been made to include the social group optimization technique into applications for watermark embedding, to our knowledge. The SGO method can assist in striking a balance between various watermarking qualities. To demonstrate the utility of the suggested method, it is compared to a variety of existing watermarking techniques. The approach presented here is a robust solution that may be applied to a wide variety of multimedia applications, including telemedicine, media distribution, and security systems.

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References

  1. Hu, D., Zhao, D., Zheng, S.: A new robust approach for reversible database watermarking with distortion control. IEEE Trans. Knowl. Data Eng. 31(6), 1024–1037 (2019). https://doi.org/10.1109/TKDE.2018.2851517

    Article  Google Scholar 

  2. Nambakhsh, M.-S., Ahmadian, A., Zaidi, H.: A contextual-based double watermarking of PET images by Patient ID and ECG Signal. Comput. Methods Prog. Biomed. 104, 418–25 (2010). https://doi.org/10.1016/j.cmpb.2010.08.016

    Article  Google Scholar 

  3. Kumar, S., Dutta, A.: A study on the robustness of block entropy-based digital image watermarking techniques with respect to various attacks. IEEE. 1802–1806 (2017).

  4. Garg, P., Kishore, R.: Performance comparison of various watermarking techniques. Multimed. Tools Appl. 79, 25921–25967 (2020). https://doi.org/10.1007/s11042-020-09262-1

    Article  Google Scholar 

  5. Rajani, D., Rajeshkumar, P.: An optimized blind watermarking scheme based on principal component analysis in redundant discrete wavelet domain. Signal Process. 172, 1–13 (2020). https://doi.org/10.1016/j.sigpro.2020.107556

    Article  Google Scholar 

  6. Abbasi, R., Chen, J., Al-Otaibi, Y., et al.: RDH-based dynamic weighted histogram equalization using for secure transmission and cancer prediction. Multimedia Syst. 27, 177–189 (2021). https://doi.org/10.1007/s00530-020-00718-w

    Article  Google Scholar 

  7. Yuan, Z., Su, Q., Liu, D., et al.: A blind image watermarking scheme combining spatial domain and frequency domain. Visual Comput. 37, 1867–1881 (2021). https://doi.org/10.1007/s00371-020-01945-y

    Article  Google Scholar 

  8. Abbasi, R., Xu, L., Amin, F., Bin, L.: Efficient lossless compression based reversible data hiding using multilayered n-bit localization. Security Commun. Netw. 2019, 1–13 (2019). https://doi.org/10.1155/2019/8981240

    Article  Google Scholar 

  9. Chamlawi, R., Ali, H.: Intelligent watermarking scheme for image authentication and recovery. Int. J. Adv. Comput. Sci. Appl. (2017). https://doi.org/10.14569/IJACSA.2017.080527

    Article  Google Scholar 

  10. Sharmin, S., Khaliluzzaman, M., Mahiuddin, M., Kafi, A.: Blind Digital Image Watermarking for Copyright Protection Based on Hadamard Transform: Proceedings of IEMIS 2018, Volume 3 (2019). https://doi.org/10.1007/978-981-13-1501-5_18.

  11. Khare, P., Srivastava, V.: A reliable and secure image watermarking algorithm using a homomorphic transform in DWT domain. Multidimen. Syst. Signal Process. (2021). https://doi.org/10.1007/s11045-020-00732-1

    Article  MathSciNet  MATH  Google Scholar 

  12. Prasanthvaidya, S., Chandramouli, P.V.: A robust semi-blind watermarking for color images based on multiple decompositions. Multimed. Tools Appl. (2017). https://doi.org/10.1007/s11042-017-4355-0

    Article  Google Scholar 

  13. Parah, S., Sheikh, J., Loan, N., Bhat, G.: Robust and Blind Watermarking Technique in DCT Domain using Inter-block Coefficient Differencing, pp. 1–25. Digital signal Process Elsevier, Amsterdem (2016)

    Google Scholar 

  14. Hong, W., Hang, M.: Robust digital watermarking scheme for copy right protection. IEEE Trans. Signal Process 12, 1–8 (2006)

    Google Scholar 

  15. Dey, N., Rajinikanth, V., Ashour, A.S., Tavares, J.: Social group optimization supported segmentation and evaluation of skin melanoma images. Symmetry 10, 51 (2018). https://doi.org/10.3390/sym10020051

    Article  MATH  Google Scholar 

  16. Singh, A.: Improved hybrid algorithm for robust and imperceptible multiple watermarking using digital images, pp. 1–18. Multimedia Tools Application Springer, Berlin pp (2015)

    Google Scholar 

  17. Mata-Mendoza, D., Cedillo-Hernandez, M., Garcia-Ugalde, F., et al.: Secured telemedicine of medical imaging based on dual robust watermarking. Visual Comput. (2021). https://doi.org/10.1007/s00371-021-02267-3

    Article  Google Scholar 

  18. Issa, M.: Digital image watermarking performance improvement using bio-inspired algorithms. Adv. Soft Comput. Mach. Learn. Image Process. Stud. Comput. Intell. 730, 683–698 (2018)

    Google Scholar 

  19. Luo, A., Zou, W.: Secure and robust watermark scheme based on multiple transforms and particle swarm optimization algorithm. Multimed. Tools Appl. 78, 1–17 (2018)

    Google Scholar 

  20. Verma, V., Srivastava, V., Thakkar, F.: DWT-SVD based digital image watermarking using swarm intelligence. In: International Conference on Electrical, Electronics, and Optimization Techniques IEEE:3198–3203 (2016).

  21. Vishwakarma, V., Sisaudia, V.: Gray-scale image watermarking based on DE-KELM in DCT domain. Proc. Comput. Sci. 132, 1012–1020 (2018)

    Article  Google Scholar 

  22. Zheng, W.: Robust and high capacity watermarking for image-based on DWT-SVD and CNN. In: 13th IEEE Conference on Industrial Electronics and Applications (ICIEA) Wuhan: 1233–1237 (2018).

  23. Mehta, R., Rajpal, N., Vishwakarma, V.: LWT- QR decomposition-based robust and efficient image watermarking scheme using Lagrangian SVR. Multimed. Tools Appl. 75(7), 4129–4150 (2016)

    Article  Google Scholar 

  24. Garg P., Kishore R. R.: Literature Review of Various Nature-Inspired Optimization Algorithms Used for Digital Watermarking. In: Singh V., Asari V.K., Kumar S., Patel R.B. (eds) Computational Methods and Data Engineering. Advances in Intelligent Systems and Computing, vol 1257. Springer, Singapore (2021). doi: https://doi.org/10.1007/978-981-15-7907-3_3

  25. Fazli, S., Moeini, M.: A robust image watermarking method based on DWT, DCT, and SVD using a new technique for correction of main geometric attacks. Optik Int. J. Light Electron. Opt. (2015). https://doi.org/10.1016/j.ijleo.2015.09.205

    Article  Google Scholar 

  26. Maloo, S., Kumar, M., Lakshmi, N.: A modified whale optimization algorithm based digital image watermarking approach. Sens. Imag. (2020). https://doi.org/10.1007/s11220-020-00291-6

    Article  Google Scholar 

  27. Sam, J.R., Edward, J., Ramu, P., Swaminathan, R.: Imperceptibility – robustness tradeoff studies for ECG steganography using continuous ant colony optimization. Expert Syst. Appl. (2015). https://doi.org/10.1016/j.eswa.2015.12.010

    Article  Google Scholar 

  28. Ebrahimi Moghaddam, M., Yazdanbakhsh, F.: A robust HDR images watermarking method using artificial bee colony algorithm. J. Inf. Secur. Appl. 41, 12–27 (2018). https://doi.org/10.1016/j.jisa.2018.05.003

    Article  Google Scholar 

  29. Su, Q., Wang, G., Zhang, X., Lv, G., Chen, B.: A new algorithm of blind color image watermarking based on LU decomposition. Multidimen. Syst. Signal Process. (2018). https://doi.org/10.1007/s11045-017-0487-7

    Article  MathSciNet  MATH  Google Scholar 

  30. Thakkar, F., Srivastava, V.: Performance comparison of recent optimization algorithm Jaya with particle swarm optimization for digital image watermarking in the complex wavelet domain. Multidimen. Syst. Signal Process. (2019). https://doi.org/10.1007/s11045-018-0627-8

    Article  MATH  Google Scholar 

  31. Aditya, K., Choudhary, A., Raj, A., Sing, M., Adhikari, A.: Image watermarking based on a cuckoo search with dwt using lévy flight algorithms. 29–33 (2017). https://doi.org/10.1109/NETACT.2017.8076737.

  32. Sundararajana, M., Yamuna, G.: Optimization of colour image watermarking using area of best fit equation and cuckoo search algorithm. Mater. Today Proc. 5, 1138–1146 (2018)

    Article  Google Scholar 

  33. Nerurkar, P., Phadke, A.: Digital image watermarking using firefly algorithm. IEEE. 1–5 (2018). https://doi.org/10.1109/ICCUBEA.2018.8697666.

  34. Sejpal, S., Shah: A novel multiple objectives optimized color watermarking scheme based on LWT-SVD domain using nature-based bat algorithm and firefly algorithm. In: IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT), pp. 38–44 (2016). https://doi.org/10.1109/ICAECCT.2016.7942552.

  35. Moeinaddini, E.: Selecting optimal blocks for image watermarking using entropy and distinct discrete firefly algorithm. Soft Comput. (2019). https://doi.org/10.1007/s00500-018-3535-9

    Article  Google Scholar 

  36. Abdelhakim, A., Saleh, H., Nassar, A.: A quality guaranteed robust image watermarking optimization with Artificial Bee Colony. Exp. Syst. Appl. 72, 317–326 (2016)

    Article  Google Scholar 

  37. Allam, M.: Distinctive Data Hiding with Image Watermarking using Bezier Curves. (2014). https://doi.org/10.13140/2.1.2154.1121.

  38. Uzma, B., Muhammad, A., Jamaludin, M.A.: The G2 and C2 rational quadratic trigonometric Bézier curve with two shape parameters with applications. Appl. Math. Comput. 219(20), 10183–10197 (2013). https://doi.org/10.1016/j.amc.2013.03.110

    Article  MathSciNet  MATH  Google Scholar 

  39. Bibi, S., Abbas, M., Misro, M.Y., Hu, G.: A Novel approach of hybrid trigonometric bézier curve to the modeling of symmetric revolutionary curves and symmetric rotation surfaces. IEEE Access, pp. 1–10 (2019). https://doi.org/10.1109/ACCESS.2019.2953496.

  40. Usman, M., Abbas, M., Miura, K.: Some engineering applications of new trigonometric cubic Bézier-like curves to free-form complex curve modeling. J. Adv. Mech. Des. Syst. Manuf. 14, 1–15 (2020). https://doi.org/10.1299/jamdsm.2020jamdsm0048

    Article  Google Scholar 

  41. Abbas, M., Ramli, N., Majid, A.A., Ali, J.M.: The representation of circular arc by using rational cubic timmer curve. Math. Prob. Eng. (2014). https://doi.org/10.1155/2014/408492

    Article  MathSciNet  MATH  Google Scholar 

  42. Maqsood, S., Abbas, M., Hu, G., Ramli, A.L.A., Miura, K.T.: A Novel generalization of trigonometric bézier curve and surface with shape parameters and its applications. Math. Prob. Eng. (2020). https://doi.org/10.1155/2020/4036434

    Article  Google Scholar 

  43. BiBi, S., Abbas, M., Miura, K.T., Misro, M.Y.: Geometric modeling of novel generalized hybrid trigonometric bézier-like curve with shape parameters and its applications. Mathematics (2020). https://doi.org/10.3390/math8060967

    Article  Google Scholar 

  44. Majeed, A., Abbas, M., Miura, K.T., Kamran, M., Nazir, T.: Surface modeling from 2D contours with an application to craniofacial fracture construction. Mathematics. 8, 1246 (2020). https://doi.org/10.3390/math8081246

    Article  Google Scholar 

  45. Maqsood, S., Abbas, M., Miura, K.T., et al.: Geometric modeling and applications of generalized blended trigonometric Bézier curves with shape parameters. Adv. Differ. Equ. (2020). https://doi.org/10.1186/s13662-020-03001-4

    Article  MATH  Google Scholar 

  46. Satapathy, S., Naik, A.: Social group optimization (SGO): a new population evolutionary optimization technique. Complex Intell. Syst. (2016). https://doi.org/10.1007/s40747-016-0022-8

    Article  Google Scholar 

  47. Feng, X., Wang, Y., Yu, H., Luo, F.: A novel intelligence algorithm based on the social group optimization behaviors. IEEE Trans. Syst. Man Cybern. Syst. (2016). https://doi.org/10.1109/TSMC.2016.2586973

    Article  Google Scholar 

  48. Naik, A., Satapathy, S., Abraham, A.: Modified Social Group Optimization-a meta-heuristic algorithm to solve short-term hydrothermal scheduling. Appl. Soft Comput. 95, 106524 (2020). https://doi.org/10.1016/j.asoc.2020.106524

    Article  Google Scholar 

  49. Perwej, Y., Parwej, F., Perwej, A.: An adaptive watermarking technique for the copyright of digital images and digital image protection. Int. J. Multimed. Appl. 4(2), 21–38 (2012)

    Google Scholar 

  50. Dubolia, R., Singh, R., Bhadoria, S., Gupta, R.: Digital image watermarking by using discrete wavelet transform and discrete cosine transform and comparison based on PSNR. In: IEEE International Conference on Communication Systems and Network Technologies pp. 593–596 (2011).

  51. Xu, H., Kang, X., Wang, Y., Wang, Y.: Exploring robust and blind watermarking approach of color images in DWT-DCT-SVD domain for copyright protection. Indersci. Int. J. Electron. Secur. Digital Forensics 10(1), 79–96 (2018)

    Article  Google Scholar 

  52. Data Source. Online available at [http://decsai.ugr.es/cvg/CG/base.htm] accessed on 29–5–2021

  53. Nguyen, P.-B., Luong, M., Beghdadi, A.: Statistical analysis of image quality metrics for watermark transparency assessment. 6297. 685–696 (2010).

  54. Enrico M., Florent A., Patrick Le C., Patrizio C.: Evaluation of standard watermarking techniques. electronic imaging, security, steganography, and watermarking of multimedia contents, San Jose, United States. 6505–24 (2007).

  55. Al-Nabhani, Y., Jalab, H., Wahid, A., Md. Noor, R.: Robust watermarking algorithm for digital images using discrete wavelet and probabilistic neural network. J. King Saud University – Comput. Inf. Sci. 27 (2015).

  56. Sun, L., Xu, J., Liu, S., Zhang, S., Li, Y., Shen, C.: A robust image watermarking scheme using Arnold transform and BP neural network. Neural Comput. Appl. (2018). https://doi.org/10.1007/s00521-016-2788-4

    Article  Google Scholar 

  57. Zear, A., Singh, A., Pardeep Kumar: A proposed secure multiple watermarking techniques based on DWT, DCT, and SVD for application in medicine. Multimedia Tools Application Springer, pp. 1–20 (2016).

  58. Ali, M., Ahn, C.W.: An optimal image watermarking approach through a cuckoo search algorithm in the wavelet domain. Int. J. Syst. Assurance Eng. Manag. (2014). https://doi.org/10.1007/s13198-014-0288-4

    Article  Google Scholar 

  59. Liu, D., Qingtang, Su., Yuan, Z., Zhang, X.: A fusion-domain color image watermarking based on Haar transform and image correction. Expert Syst. Appl. 170(114540), 1–12 (2021). https://doi.org/10.1016/j.eswa.2020.114540

    Article  Google Scholar 

  60. Bagheri Baba Ahmadi, S., Zhang, G., Wei, S., et al.: An intelligent and blind image watermarking scheme based on hybrid SVD transforms using human visual system characteristics. Visual Comput. 37, 385–409 (2021). https://doi.org/10.1007/s00371-020-01808-6

    Article  Google Scholar 

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  1. University School of Information, Communication & Technology, Guru Gobind Singh Indraprastha University, Dwarka, New Delhi, India

    Preeti Garg & R. Rama Kishore

  2. KIET Group of Institutions, Delhi-NCR, Ghaziabad, India

    Preeti Garg

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Garg, P., Rama Kishore, R. A robust and secured adaptive image watermarking using social group optimization. Vis Comput 39, 4839–4854 (2023). https://doi.org/10.1007/s00371-022-02631-x

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