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A novel semi fragile watermarking technique for tamper detection and recovery using IWT and DCT

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Abstract

A novel semi fragile watermarking technique using integer wavelet transform (IWT) and discrete cosine transform (DCT) for tamper detection and recovery to enhance enterprise multimedia security is proposed. In this paper, two types of watermark are generated which are namely the authentication watermark and recovery Watermark. The Watermarked Image is formed by embedding the authentication watermark which is generated using the proposed IWT based authentication watermark generating Technique. Next, the watermarked image is divided into 2 × 2 blocks and a 10 bit recovery watermark is generated from each of the 2 × 2 blocks using the proposed DCT based recovery watermark generation technique. The generated recovery watermark is used to form the recovery tag which is sent along with the watermarked image to the receiver. At the receiver side, the proposed tamper detection technique is used for verifying the authenticity and identifying the attacks in the watermarked image. If the manipulations are identified as malicious, then the tampered parts in the received image are recovered using the proposed tamper recovery technique. The performance of the proposed tamper detection and recovery technique was tested for different types of incidental/content preserving manipulations and various types of malicious attacks. When compared to the existing semi fragile watermarking techniques, the proposed embedding technique produced a better PSNR (Peak Signal to noise ratio) for various watermarked images. Also, the proposed tamper detection and recovery technique were able to localize the malicious attacks and subsequently recover the tampered parts when compared to the existing techniques. The increased performance of the proposed tamper detection and recovery technique was due to the usage of both Normalized Hamming Similarity (NHS) and tamper detection map in the proposed tamper detection technique to identify manipulations and due to the generation of both the authentication and recovery watermark.

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References

  1. 1.

    Anwar S, Zain J-M, Zolkipli M-F, Inayat Z, Khan S, Anthony B, Chang V (2017) From intrusion detection to an intrusion response system: fundamentals, requirements and future directions. Algorithms 10(2):39

  2. 2.

    Zerdoumi S, Sabri A-Q-M, Kamsin A, Hashem I-A-T, Gani A, Hakak S, Algarandi M-A, Chang V (2018) Image pattern recognition in big data: taxonomy and open challenges: survey. Multimed Tools Appl 77:10091–10121

  3. 3.

    Duncan B, Whittington M, Chang V (2017) Enterprise security and privacy: why adding IoT and big data makes it so much more difficult. In: 2017 international conference on engineering and technology (ICET), 2017, August. IEEE, pp 1–7

  4. 4.

    Yang Y, Zheng X, Guo W, Liu X, Chang V (2019) Privacy-preserving smart IoT-based healthcare big data storage and self-adaptive access control system. Inf Sci 479:567–592

  5. 5.

    Kuo C-T, Chi P-W, Chang V, Lei C-L (2018) SFaaS: keeping an eye on IoT fusion environment with security fusion as a service. Future Gen Comput Syst 86:1424–1436

  6. 6.

    Kang H, Park JH (2003) A semi-fragile watermarking using JND. In: Proceedings of the Pacific Rim workshop on digital steganography (STEG 2003), pp 127–131

  7. 7.

    Hu YP, Han DZ (2005) Using two semi-fragile watermarks for image authentication. In: Proceedings of the fourth international conference on machine learning and cybernetics, Guangzhou, China, pp 5484–5489

  8. 8.

    Liu H, Lin J, Huang J (2005) Image authentication using content based watermark. In: Proceedings of IEEE international symposium on circuits and systems, Kobe, Japan, pp 4014–4017

  9. 9.

    Yang H, Sun X (2008) Semi-fragile watermarking for image authentication and tamper detection using HVS model. In: Proceedings of international conference on multimedia and ubiquitous engineering, Seoul, South Korea, pp 1112–1117

  10. 10.

    Preda RO (2013) Semi-fragile watermarking for image authentication with sensitive tamper localization in the wavelet domain. Measurement 46(1):367–373

  11. 11.

    Tsai MJ, Chien CC (2008) A wavelet-based semi-fragile watermarking with recovery mechanism. In: Proceedings of the IEEE international symposium on circuits and systems, Seattle, WA, USA, pp 3033–3036

  12. 12.

    Preda RO, Marcu I, Ciobanu A (2015) Image authentication and recovery using wavelet-based dual watermarking. UPB Sci Bull Ser C 77(4):199–212

  13. 13.

    Tiwari A, Sharma M, Tamrakar RK (2017) Watermarking based image authentication and tamper detection algorithm using vector quantization approach. AEU-Int J Electron Commun 78:114–123

  14. 14.

    Benrhouma O, Hermassi H, Belghith S (2015) Tamper detection and self-recovery scheme by DWT watermarking. Nonlinear Dyn 79(3):1817–1833

  15. 15.

    Lai CC (2011) A digital watermarking scheme based on singular value decomposition and tiny genetic algorithm. Digit Signal Proc 21(4):522–527

  16. 16.

    Lu ZM, Xu DG, Sun SH (2005) Multipurpose image watermarking algorithm based on multistage vector quantization. IEEE Trans Image Process 14(6):822–831

  17. 17.

    Voloshynovskiy S, Pereira S, Pun T, Eggers JJ, Su JK (2001) Attacks on digital watermarks: classification, estimation based attacks and benchmarks. IEEE Commun Mag 39(8):118–126

  18. 18.

    Shen H, Chen B (2012) From single watermark to dual watermark: a new approach for image watermarking. Comput Electr Eng 38(5):1310–1324

  19. 19.

    Li C, Zhang A, Liu Z, Liao L, Huang D (2015) Semi-fragile self-recoverable watermarking algorithm based on wavelet group quantization and double authentication. Multimed Tools Appl 74(23):10581–10604

  20. 20.

    Zhang Z, Wang C, Zhou X (2016) Image watermarking scheme based on DWT-DCT and SSVD. Int J Secur Appl 10(10):191–206

  21. 21.

    Shojanazeri H, Adnan WAW, Ahmad SMS, Rahimipour S (2017) Authentication of images using Zernike moment watermarking. Multimed Tools Appl 76(1):577–606

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Correspondence to Nandhini Sivasubramanian.

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Sivasubramanian, N., Konganathan, G. A novel semi fragile watermarking technique for tamper detection and recovery using IWT and DCT. Computing (2020). https://doi.org/10.1007/s00607-020-00797-7

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Keywords

  • Semi fragile watermarking
  • Integer wavelet transform
  • Image processing
  • Tamper detection
  • Tamper recovery
  • Enterprise multimedia security

Mathematics Subject Classification

  • 68U10
  • 94A08