Skip to main content
Log in

Image authentication and tamper localization based on relative difference between DCT coefficient and its estimated value

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Digital images are increasingly transmitted over non-secure channels such as Internet, therefore image authentication techniques have recently gained great attention due to their importance for a large number of multimedia applications. To protect the authenticity of images, several approaches have been proposed. These approaches include conventional cryptography, semi-fragile watermarking and digital signatures. In this paper, we propose two techniques of the same type based on what we call characteristic data digest. Both techniques can blindly detect and localize malicious tampering, while maintaining reasonable tolerance to conventional content-preserving manipulations. The characteristic data is derived from the relative difference between each pair of selected DCT coefficient, AC for one technique and DC for another technique, in a central block and its counterpart estimated by the center block and its adjacent blocks. In order to maintain the relative difference relationship when the image undergoes legitimate processing, we make a pre-compensation for the coefficients. Experimental results show that our techniques are significantly superior to semi-fragile techniques under the condition of the same image fidelity, especially in tolerance range of legitimate processing, and/or the ability to detect and localize the tampered area. Due to the simplicity of the algorithms, our techniques can be used in video frame authentication, and even other digital media. In addition, this kind of proposed techniques can be extended to use other characteristic data, such as high-level moment, statistical data of images, and so on.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

References

  1. Andres F (2001) Multimedia and security. IEEE Trans Multimed 8(4):20–21

    Article  Google Scholar 

  2. Battiato S, Maria G, Messina F, Puglisi G (2002) Robust Image Alignment for Tampering Detection. IEEE Trans Inf Forensics Secur 7(4):1105–1117

    Article  Google Scholar 

  3. Bennett W (1970) Introduction to Signal Transmission (Electrical & Electronic Engineering), 1st edn. McGraw-Hill Inc., New York, pp 100–110

    Google Scholar 

  4. Cao H, Kot AC (2013) On Establishing Edge Adaptive Grid for Bi-level Image Data Hiding. IEEE Trans Inf Forensics Secur 8(9):1508–1518

    Article  Google Scholar 

  5. CASIA (2017) Available: http://forensics.idealtest.org/ Accessed 28 Dec 2017

  6. Dittmann J, Steinmetz A, Steinmetz R (1999) Content-based digital signature for motion pictures authentication and content-fragile watermarking. In: Proc. IEEE Int. Conf. Multimedia Computing and Systems, vol II. IEEE Computer Society, New York, pp 209–213

    Chapter  Google Scholar 

  7. Fei C, Kundur D, Kwong RH (2006) Analysis and design of secure watermark-based authentication systems. IEEE Trans Inf Forensics Secur 1(1):43–55

    Article  Google Scholar 

  8. Feng W, Liu ZQ (2008) Region-Level Image Authentication Using Bayesian Structural Content Abstraction. IEEE Trans Image Process 17(12):2413–2424

    Article  MathSciNet  Google Scholar 

  9. Gonzales CA, Allman L, Mccarthy T (1990) DCT coding for motion video storage using adaptive arithmetic coding. Signal Process Image Commun 2(2):145–154

    Article  Google Scholar 

  10. Guzman AM, Goryawala M, Wang J, Adjouadi M (2013) Thermal Imaging as a Biometrics Approach to Facial Signature Authentication. IEEE J Biomed Health Informatics 17(1):214–222

    Article  Google Scholar 

  11. Haouzia A, Noumeir R (2008) Methods for image authentication: a survey. Multimed Tool Appl 1(39):1–46

    Article  Google Scholar 

  12. Lampson B, Rivest R (1997) Cryptography and information security group research project: a simple distributed security infrastructure. Technical report, MIT. http://www.people.csail.mit.edu/rivest/pubs.html#RL96

  13. Lin C-Y, Chang S-F (2001) A robust image authentication method distinguishing JPEG compression from malicious manipulation. IEEE Trans Circuits Syst Video Technol 11(2):153–168

  14. Lin C, Chang S (2010) Semi-fragile watermarking for authenticating JPEG visual content. Proc. SPIE 3971, Security and Watermarking of Multimedia Contents II, (9 May 2000). https://doi.org/10.1117/12.384968

  15. Lin ET, Podilchun CI, Delp EJ (2000) Detection of image alterations using semi-fragile watermarks. Proc. SPIE 3971, Security and Watermarking of Multimedia Contents II, (9 May 2000). https://doi.org/10.1117/12.384969

  16. Liu S, Lu M, Liu G, Pan Z (2017) A novel distance metric: generalized relative entropy. Entropy 19(6):269. https://doi.org/10.3390/e19060269

    Article  Google Scholar 

  17. Liu S, Pan Z, Song H (2017) Digital image watermarking method based on DCT and fractal encoding. IET Image Process 11(10):815–821

    Article  Google Scholar 

  18. Liu S, Fu W, He L, Zhou J, Ma M (2017) Distribution of primary additional errors in fractal encoding method. Multimed Tool Appl 76(4):5787–5802

    Article  Google Scholar 

  19. Monga V, Evans BL (2006) Perceptual Image Hashing Via Feature Points: Performance Evaluation and Tradeoffs. IEEE Trans Image Process 15(11):3452–3465

    Article  Google Scholar 

  20. Nender W, Gruhl D, Morimoto N, Lu A (1996) Techniques for data hiding. IBM Syst J 3:131–136

    Google Scholar 

  21. Rey C, Dugelay JL (2000) Blind detection of malicious alterations on still images using robust watermarks. Proc. IEE Secure Images and Image Authentication Colloquium, London, pp 7/1–7/6

    Google Scholar 

  22. Schneider M, Chang S-F (1996) A robust content based digital signature for image authentication. Proc IEEE Int Conf on Image Processing 3:227–230

    Article  Google Scholar 

  23. Tagliasacchi M, Valenzise G, Tubaro S (2009) Hash-Based Identification of Sparse Image Tampering. IEEE Trans Image Process 18(11):2491–2504

    Article  MathSciNet  Google Scholar 

  24. Toyokawa K, Morimoto N, Tonegawa S, Kamijo K, Koide A (2000) Secure digital photograph handling with watermarking technique in insurance claim process. Proc SPIE 3971:438–445

    Article  Google Scholar 

  25. Tse D, Viswanath P (2005) Fundamentals of wireless communication, 1st edn. Cambridge University Press, Cambridge, pp 203–210

    Book  Google Scholar 

  26. Wu CW (2012) On the design of content-based multimedia authentication systems. IEEE Trans Multimed 4(3):385–393

    Google Scholar 

  27. Yu GW, Lu CS, Liao HYM (2001) Mean quantization-based fragile watermarking for image authentication. Opt Eng 40(7):1396–1408

    Article  Google Scholar 

  28. Yuan H, Zhang XP (2006) Multi-scale Fragile Watermarking Based on the Gaussian Mixture Model. IEEE Trans Image Process 15(10):3189–3200

    Article  Google Scholar 

  29. Yuan L, Ran Q, Zhao T (2017) Image authentication based on double-image encryption and partial phase decryption in nonseparable fractional Fourier domain. Opt Laser Technol 88:111–120

    Article  Google Scholar 

  30. Zhu BB, Swanson MD, Tewfik AH (2004) When seeing isn't believing [multimedia authentication technologies]. IEEE Signal Process Mag 21(2):40–49

    Article  Google Scholar 

  31. Zhu BB, Swanson MD, Tewfik AH (2004) When seeing isn’t believing. IEEE Signal Processing Mag 21(2):40–49

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by applied basic research plan of Wuhan Science and Technology Bureau with Grant No. 2017010201010105 in China, and Shenzhen Science and Technology Innovation Committee with Grant No. JCYJ20170306170559215 in China.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yulin Wang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ding, W., Xie, Y. & Wang, Y. Image authentication and tamper localization based on relative difference between DCT coefficient and its estimated value. Multimed Tools Appl 78, 5305–5328 (2019). https://doi.org/10.1007/s11042-018-5732-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-018-5732-z

Keywords

Navigation