10.57647/j.mjee.2024.1802.38

Integrating encryption and watermarking for enhanced information transmission security

HTML PDF
  • Hadi Nazari1,
  • Mahmoud Mahlouji Bidgoli*1,
  • Hossein Ghasvari1,
  1. Department of Electrical and Telecommunication Engineering, Kashan Branch, Islamic Azad University, Kashan, Iran
Integrating encryption and watermarking for enhanced information transmission security

Published 2024-06-03

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Nazari, H., Mahlouji Bidgoli, M., & Ghasvari, H. (2024). Integrating encryption and watermarking for enhanced information transmission security. Majlesi Journal of Electrical Engineering, 18(2). https://doi.org/10.57647/j.mjee.2024.1802.38
Crossref
Scopus
Google Scholar
Europe PMC

HTML views: 4

PDF views: 54

Abstract

With the digital world booming, so too has the importance of information security. Ensuring safe transmission of data has become paramount, requiring robust mechanisms to navigate potential vulnerabilities. In this context, encryption and watermarking technologies emerge as key players. This article proposes a groundbreaking method that seamlessly integrates a lightweight encryption scheme with a dedicated watermarking approach for color images. Our proposed technique boasts two key advantages: efficient encryption and successful watermark concealment. The chosen encryption method is computationally light, meaning it requires minimal processing power, yet still effectively shields the embedded watermark. This watermarking process involves a clever two-step transformation. First, the color image is converted into a different color space using the Triangle Vertex Transform (TVT). This lays the groundwork for the second step, where the watermark itself is embedded. For this, we leverage a clever combination of the 2-level Discrete Wavelet Transform (DWT) and the Discrete Cosine Transform (DCT). To gauge the effectiveness of this innovative approach, we put it to the test using popular color images and evaluated it through various metrics. These include standard measures like histogram analysis, correlation, Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM). These metrics help us understand the success of both the encryption and watermarking aspects. The results speak for themselves: our proposed method achieves an impressive PSNR of 54.4798 dB and a near-perfect SSIM score of 1. This translates to a watermarked image with exceptional quality, practically indistinguishable from the original. Ultimately, this research presents a novel technique that shines in both robustness and imperceptibility, outperforming many existing state-of-the-art methods. This paves the way for safeguarding information with greater efficiency and accuracy, enhancing the reliability of our digital interactions in an increasingly interconnected world.

Keywords

  • DCT,
  • DWT,
  • Encryption,
  • Information security,
  • Triangle Vertex Transform (TVT),
  • Watermarking
HTML PDF

References

  1. A. Mpatziakas, A. Drosou, S. Papadopoulos, and D. Tzovaras. “IoT threat mitigation engine em- powered by artificial intelligence multi-objective optimization.”. Journal of Network and Computer Applications, 203:pp. 103398, 2022.
  2. K. Sorri, N. Mustafee, and M. Seppa¨nen. “Revisiting IoT definitions: A framework towards compre- hensive use.”. Technological Forecasting and Social Change, 179:pp. 121623, 2022.
  3. E. Schiller, A. Aidoo, J. Fuhrer, J. Stahl, M. Zio¨ rjen, and B. Stiller. “Landscape of IoT security.”. Com- puter Science Review, 44:pp. 100467, 2022.
  4. V. K. Quy. “IoT-enabled smart agriculture: Ar- chitecture, applications, and challenges.”. Applied Sciences, 12(7):pp. 3396, 2022.
  5. A. Sreedevi, T. N. Harshitha, V. Sugumaran, and P. Shankar. “Application of cognitive computing in healthcare, cybersecurity, big data and IoT: A literature review.”. Information Processing & Man- agement, 59(2):pp. 102888, 2022.
  6. I. H. Sarker, A. I. Khan, Y. B. Abushark, and F. Also- lami. “Internet of things (iot) security intelligence: A comprehensive overview, machine learning so- lutions and research directions.”. Mobile Networks and Applications, 28(1):pp. 296–312, 2023.
  7. P. K. Sadhu, V. P. Yanambaka, and A. Abdelgawad. “Internet of things: Security and solutions survey.”. Sensors, 22(19):pp. 7433, 2022.
  8. K. N. Singh and A. K. Singh. “Towards integrating image encryption with compression: A survey.”. ACM Transactions on Multimedia Computing, Com- munications, and Applications (TOMM), 18(3):pp. 1– 21, 2022.
  9. U. Zia. “Survey on image encryption techniques using chaotic maps in spatial, transform and spa- tiotemporal domains. ”. International Journal of Information Security, 21(4):pp. 917–935, 2022.
  10. S. Roy, U. Rawat, H. A. Sareen, and S. K. Nayak. “IECA: an efficient IoT friendly image encryption technique using programmable cellular automata.”. Journal of Ambient Intelligence and Humanized Com- puting, 11:pp. 5083–5102, 2020.
  11. H. Dweik and M. Abutaha. “A survey of lightweight image encryption for IoT.”. Lightweight Crypto- graphic Techniques and Cybersecurity Approaches: IntechOpen, , 2022.
  12. S. Roy, M. Shrivastava, C. V. Pandey, S. K. Nayak, and U. Rawat. “IEVCA: An efficient image encryp- tion technique for IoT applications using 2-D Von- Neumann cellular automata.”. Multimedia Tools and Applications, 80:pp. 31529–31567, 2021.
  13. D. Trujillo-Toledo. “Real-time medical image en- cryption for H-IoT applications using improved sequences from chaotic maps.”. Integration, 90:pp. 131–145, 2023.
  14. M. Devipriya and M. Brindha. “Image encryption using modified perfect shuffle-based bit level per- mutation and learning with errors based diffusion for IoT devices.”. Computers and Electrical Engi- neering, 100:pp. 107954, 2022.
  15. T. A. Dhopavkar, S. K. Nayak, and S. Roy. “IETD: A novel image encryption technique using Tinker- bell map and Duffing map for IoT applications.”. Multimedia Tools and Applications, 81(30):pp. 43189–43228, 2022.
  16. M. Begum and M. S. Uddin. “igital image water- marking techniques: A review.”. Information, 11(2):pp. 110, 2020.
  17. R. Wazirali, R. Ahmad, A. Al-Amayreh, M. Al-Madi, and A. Khalifeh. “Secure watermarking schemes and their approaches in the IoT technology: An overview.”. Electronics, 10(14):pp. 1744, 2021.
  18. O. P. Singh, A. Anand, A. K. Agrawal, and A. K. Singh. “Electronic health data security in the in- ternet of things through watermarking: An intro- duction.”. IEEE Internet of Things Magazine, 5(2):pp. 55–58, 2022.
  19. M. Begum and M. S. Uddin. “Towards the develop- ment of an effective image watermarking system.”. Security and Privacy, 5(2):pp. e196, 2022.
  20. W. Wan, J. Wang, Y. Zhang, J. Li, H. Yu, and J. Sun. “A comprehensive survey on robust image water- marking.”. Neurocomputing, 488:pp. 226–247, 2022.
  21. N. D. Pulgam and S. K. Shinde. “Robust digital watermarking using pixel color correlation and chaotic encryption for medical image protection.”. International Journal of Intelligent Systems and Appli- cations in Engineering, 10(4):pp. 29–38, 2022.
  22. D. K. Mahto and A. K. Singh. “A survey of color im- age watermarking: State-of-the-art and research directions.”. Computers & Electrical Engineering, 93:pp. 107255, 2021.
  23. K. J. Giri, S. Quadri, R. Bashir, and J. I. Bhat. “DWT based color image watermarking: A review.”. Mul- timedia Tools and Applications, 79:pp. 32881–32895, 2020.
  24. C. Tiken and R. Samli. “A comprehensive review about image encryption methods.”. Harran U¨ niver- sitesi Mu¨hendislik Dergisi, 7(1):pp. 27–49, 2022.
  25. J. Arif. “A novel chaotic permutation-substitution image encryption scheme based on logistic map and random substitution.”. IEEE Access, 10:pp. 12966–12982, 2022.
  26. S. F. Raza and V. Satpute. “A novel bit permutation- based image encryption algorithm.”. Nonlinear Dy- namics, 95:pp. 859–873, 2019.
  27. M. Kumar, A. Saxena, and S. S. Vuppala. “A survey on chaos based image encryption techniques.”. Mul- timedia Security Using Chaotic Maps: Principles and Methodologies, :pp. 1–26, 2020.
  28. R. Ge, G. Yang, J. Wu, Y. Chen, G. Coatrieux, and L. Luo. “A novel chaos-based symmetric image en- cryption using bit-pair level process.”. IEEE Access, 7:pp. 99470–99480, 2019.
  29. S. Noshadian, A. Ebrahimzade, and S. J. Kazemitabar. “Breaking a chaotic image encryption algorithm.”. Multimedia Tools and Applications, 79:pp. 25635– 25655, 2020.
  30. M. Kaur and V. Kumar. “A comprehensive review on image encryption techniques.”. Archives of Compu- tational Methods in Engineering, 27:pp. 15–43, 2020.
  31. W. El-Shafai, F. Khallaf, E.-S. M. El-Rabaie, and F. E. A. El-Samie. “Robust medical image encryp- tion based on DNA-chaos cryptosystem for secure telemedicine and healthcare applications.”. Journal of Ambient Intelligence and Humanized Computing, 12:pp. 9007–9035, 2021.
  32. X. Yan, X. Wang, and Y. Xian. “Chaotic image en- cryption algorithm based on arithmetic sequence scrambling model and DNA encoding operation.”. Multimedia Tools and Applications, 80:pp. 10949– 10983, 2021.
  33. X. Liu and C. Liu. “Quantum image encryption scheme using independent bit-plane permutation and Baker map.”. Quantum Information Processing, 22(6):262, 2023.
  34. C. Rajakumaran and R. Kavitha. “Chaos based en- cryption of quantum images.”. Multimedia Tools and Applications, 79:pp. 23849–23860, 2020.
  35. G. Ye, K. Jiao, and X. Huang. “Quantum logistic image encryption algorithm based on SHA-3 and RSA.”. Nonlinear Dynamics, 104:pp. 2807–2827, 2021.
  36. M. A. Wani and B. Sultan. “Deep learning based image steganography: A review.”. Wiley Interdisci- plinary Reviews: Data Mining and Knowledge Dis- covery, 13(3):pp. e1481, 2023.
  37. C. Lakshmi, K. Thenmozhi, J. B. B. Rayappan, S. Rajagopalan, R. Amirtharajan, and N. Chi- dambaram. “Neural-assisted image-dependent en- cryption scheme for medical image cloud storage.”. Neural Computing and Applications, 33:pp. 6671– 6684, 2021.
  38. Y. Ding. “DeepEDN: A deep-learning-based image encryption and decryption network for internet of medical things.”. IEEE Internet of Things Journal, 8 (3):pp. 1504–1518, 2020.
  39. M. Begum and M. S. Uddin. “Analysis of digital image watermarking techniques through hybrid methods.”. Advances in Multimedia, 2020:pp. 1–12, 2020.
  40. S. B. B. Ahmadi, G. Zhang, and S. Wei. “Robust and hybrid SVD-based image watermarking schemes: A survey.”. Multimedia tools and Applications, 79:pp. 1075–1117, 2020.
  41. Q. Su, X. Zhang, and H. Wang. “A blind color image watermarking algorithm combined spatial domain and SVD.”. International Journal of Intelligent Sys- tems, 37(8):pp. 4747–4771, 2022.
  42. Q. Su and B. Chen. “Robust color image water- marking technique in the spatial domain.”. Soft Computing, 22:pp. 91–106, 2018.
  43. C. Patvardhan, P. Kumar, and C. Vasantha Lakshmi. “Effective color image watermarking scheme using YCbCr color space and QR code.”. Multimedia Tools and Applications, 77:pp. 12655–12677, 2018.
  44. X. Liu, Y. Wu, Z. Shao, J. Wu, and H. Shu. “Color im- age watermarking using a discrete trinion Fourier transform.”. Journal of Electronic Imaging, 27(4):pp. 043046–043046, 2018.
  45. S. Kumar and B. K. Singh. “An improved water- marking scheme for color image using alpha blend- ing.”. Multimedia Tools and Applications, 80:pp. 13975–999, 2021.
  46. S. Kumar and B. K. Singh. “DWT based color image watermarking using maximum entropy.”. Multime- dia Tools and Applications, 80:pp. 15487–510, 2021.
  47. X. Zhang and Q. Su. “A spatial domain-based color image blind watermarking scheme integrating mul- tilevel discrete Hartley transform.”. International Journal of Intelligent Systems, 36(8):pp. 4321–4345,
  48. K. Prabha and I. S. Sam. “A novel blind color image watermarking based on Walsh Hadamard Trans- form.”. Multimedia Tools and Applications, 79:pp. 6845–6869, 2020.
  49. H. Nazari, M. M. Bidgoli, and H. Ghasvari. “Integration of lightweight cryptography and wa- termarking with compression for high speed and reliable communication of digital images in IoT.”. IET Image Processing, , 2023.
  50. A. Benoraira, K. Benmahammed, and N. Boucenna. “Blind image watermarking technique based on dif- ferential embedding in DWT and DCT domains.”. EURASIP Journal on Advances in Signal Processing, 2015(1):pp. 1–11, 2015.
  51. J. Abraham and V. Paul. “An imperceptible spa- tial domain color image watermarking scheme.”. Journal of King Saud University-Computer and Infor- mation Sciences, 31(1):pp. 125–133, 2019.
  52. X.L. Liu, C.C. Lin, and S.M. Yuan. “Blind dual wa- termarking for color images’ authentication and copyright protection.”. IEEE Transactions on Cir- cuits and Systems for Video Technology, 28(5):pp. 1047–1055, 2016.
  53. N. A. Loan, N. N. Hurrah, S. A. Parah, J. W. Lee, J. A. Sheikh, and G. M. Bhat. “Secure and robust digital image watermarking using coefficient differencing and chaotic encryption.”. IEEE Access, 6:pp. 19876– 19897, 2018.
  54. M. Moosazadeh and G. Ekbatanifard. “An improved robust image watermarking method using DCT and YCoCg-R color space.”. Optik, 140:pp. 975– 988, 2017.
  55. M. K. Pandey, G. Parmar, R. Gupta, and A. Sikan- der. “Non-blind Arnold scrambled hybrid image watermarking in YCbCr color space.”. Microsystem Technologies, 25:pp. 3071–3081, 2019.
  56. S. Roy and A. K. Pal. “A blind DCT based color watermarking algorithm for embedding multiple watermarks.”. AEU-International Journal of Elec- tronics and Communications, 72:pp. 149–161, 2017.