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Modelling attacks on self-authentication watermarking

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Abstract

Although the Self-Authentication Watermarking (SAW) schemes are promising to tackle the multimedia information assurance problem, their unknown security level seems to impair their potential. In this paper, we identify three new counterfeiting attacks on those schemes and present their countermeasure. We develop, analyse, and validate the models of the identified attacks followed by the development of a new SAW model to resist those attacks. The identified attack models generalize three main security levels that capture all the possible counterfeiting instances. We focus on the block-wise dependent fragile watermarking schemes, and their general weaknesses. Experimental results successfully demonstrate the practicality and consequences of the identified attacks in exploiting those weaknesses to maliciously and undetectably alter valid watermarked images. To resist the identified attacks, we further determine a set of general requirements for SAW schemes and illustrate their attainment in developing an extended SAW model. While the identified attack models can be used as a means to systematically examine the security levels of similar SAW schemes, the extended SAW model may lead to developing their more secure variants. Our study has also revealed some open challenges in the development and formal analysis of SAW schemes.

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Notes

  1. Collision resistance is mainly studied for cryptographic hash functions [36]. We can informally define here a watermark as collision resistant if for a given image block, it is “hard” to find another image block, which will have the same watermark. This is a notion of “weak” collision resistance, whereas for a watermark being “strong” collision resistant, it is “hard” to find two image blocks for a given watermark. However, consideration of these different notions of collision resistance may depend on the requirements of an application scenario (see Section 7).

References

  1. Ahmed F, Siyal MY, Uddin Abbas V (2010) A secure and robust hash-based scheme for image authentication. Sig Process 90(5):1456–1470

    Article  MATH  Google Scholar 

  2. Barré S Medical image samples. http://barre.nom.fr/medical/samples/ (2003). [Online; last accessed 12-Dec-2013]

  3. Bartolini F, Tefas A, Barni M, Pitas I (2001) Image authentication techniques for surveillance applications. Proc IEEE 89:1403–1418

    Article  Google Scholar 

  4. Celik MU, Sharma G, Saber E, Tekalp AM (2002) Hierarchical watermarking for secure image authentication with localization. IEEE Trans Image Process 11(6):585–595

    Article  Google Scholar 

  5. Chang CC, Fan YH, Tai WL (2008) Four-scanning attack on hierarchical digital watermarking method for image tamper detection and recovery. Pattern Recog 41(2):654–661

    Article  MATH  Google Scholar 

  6. The USC-SIPI image database. http://sipi.usc.edu/database/ (1977). [Online; last accessed 23-Nov-2013]

  7. Dittmann J, Steinmetz A, Steinmetz R (1999) Content-based digital signature for motion pictures authentication and content-fragile watermarking. Proc ICMCS’99 2:209–213

    Google Scholar 

  8. Edupuganti VG, Shih FY, Chang IC (2012) An Efficient Block-Based Fragile Watermarking System for Tamper Localization and Recovery. CRC Press

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

    Article  Google Scholar 

  10. Fridrich J (2000) Visual hash for oblivious watermarking. In: Electronic Imaging, pp 286–294. SPIE

  11. Fridrich J, Goljan M (1999) Images with self-correcting capabilities. In: Proceedings of ICIP’99, vol 3, pp 792–796. IEEE

  12. Fridrich J, Goljan M (1999) Protection of digital images using self embedding. In: Symposium on Content Security and Data Hiding in Digital Media. Newark, NJ, USA

  13. Fridrich J, Goljan M (2000) Robust hash functions for digital watermarking. In: Proceedings of ITCC’00, pp 178–183. IEEE

  14. Fridrich J, Goljan M, Du R (2002) Lossless data embedding-new paradigm in digital watermarking. EURASIP Journal on Applied Signal Processing:185–196

  15. Fridrich J, Goljan M, Memon N (2002) Cryptanalysis of the yeung-mintzer fragile watermarking technique. Journal of Electronic Imaging 11:262–274

    Article  Google Scholar 

  16. Giry D Cryptographic key length recommendation. http://www.keylength.com/en/ (2013). [Online; last accessed 21-Nov-2013]

  17. Han SH, Chu CH (2010) Content-based image authentication: current status, issues, and challenges. Int J Inf Secur 9:19–32

    Article  Google Scholar 

  18. Haouzia A, Noumeir R (2008) Methods for image authentication: A survey. Multimedia Tools and Applications 39:1–46

    Article  Google Scholar 

  19. He H, Zhang J, Wang H (2006) Synchronous counterfeiting attacks on self-embedding watermarking schemes. Int Journal of Computer Science and Network Security 6(1B):251–257

    Google Scholar 

  20. He HJ, Zhang JS, Chen F (2009) Adjacent-block based statistical detection method for self-embedding watermarking techniques. Signal Process 89(8):1557–1566

    Article  MATH  Google Scholar 

  21. Holliman M, Memon N (2000) Counterfeiting attacks on oblivious block-wise independent invisible watermarking schemes. IEEE Trans Image Process 9:432–441

    Article  Google Scholar 

  22. Katzenbeisser S, Liu H, Steinebach M (2013) Challenges and solutions in multimedia document authentication

  23. Kutter M, Petitcolas FA (1999) Fair benchmark for image watermarking systems. In: Electronic Imaging’99, pp 226–239. SPIE

  24. Lee TY, Lin SD (2008) Dual watermark for image tamper detection and recovery. Pattern Recog 41(11):3497–3506

    Article  MATH  Google Scholar 

  25. Lie WN, Lin TI, Cheng SL (2006) Dual protection of jpeg images based on informed embedding and two-stage watermark extraction techniques. IEEE Trans on Information Forensics and Security 1(3):330–341

    Article  Google Scholar 

  26. Liew SC, Zain JM (2010) Experiment of tamper detection and recovery watermarking in picture archiving and communication systems. J Comput Sci 6:794–799

    Article  Google Scholar 

  27. Lin PL, Hsieh CK, Huang PW (2005) A hierarchical digital watermarking method for image tamper detection and recovery. Pattern Recognit 38(12):2519–2529

    Article  Google Scholar 

  28. Lin PL, Huang PW, Peng AW (2004) A fragile watermarking scheme for image authentication with localization and recovery. In: Proceedings of MSE’04, pp 146–153. IEEE

  29. Lu CS, Liao HY (2003) Structural digital signature for image authentication: an incidental distortion resistant scheme. IEEE Trans Multimedia 5(2):161–173

    Article  MathSciNet  Google Scholar 

  30. Mobasseri BG, Sieffert MJ, Simard RJ (2000) Content authentication and tamper detection in digital video. In: Proceedings of ICIP’00, vol 1, pp 458–461. IEEE

  31. Nyeem H (2014) A digital watermarking framework with application to medical image security. Ph.D. thesis, QUT, School of Electrical Eng. and Computer Science, Australia

  32. Nyeem H, Boles W, Boyd C (2011) Developing a digital image watermarking model. In: Proceedings of DICTA’11, pp 468–473. IEEE, Piscataway

    Google Scholar 

  33. Nyeem H, Boles W, Boyd C (2012) On the robustness and security of digital image watermarking. In: Proceedings of ICIEV’12. IEEE, Piscataway

    Google Scholar 

  34. Nyeem H, Boles W, Boyd C (2013) Counterfeiting attacks on block-wise dependent fragile watermarking schemes. In: Proceedings of SIN’13, pp 86–93. ACM

  35. Nyeem H, Boles W, Boyd C (2014) Digital image watermarking: its formal model, fundamental properties and possible attacks. EURASIP Journal on Advances in Signal Processing 2014(1):135. doi:10.1186/1687-6180-2014-135

    Article  Google Scholar 

  36. Paar C, Pelzl J (2010) Understanding cryptography: a textbook for students and practitioners. Springer

  37. Petitcolas FA Stirmark benchmark 4.0. http://www.petitcolas.net/fabien/Watermarking/stirmark/ (2004). [Online; last accessed 26-Mar-2014]

  38. Rey C, Dugelay JL (2002) A survey of watermarking algorithms for image authentication. EURASIP Journal on Applied Signal Processing 2002(1):613–621

    Article  MATH  Google Scholar 

  39. Sencar H, Memon N (2008) Overview of state-of-the-art in digital image forensics. Algorithms, Architectures and Information Systems Security 3:325–348

    Google Scholar 

  40. Sun Q, Chang SF (2005) A secure and robust digital signature scheme for JPEG2000 image authentication. IEEE Trans Multimedia 7(3):480–494

    Article  Google Scholar 

  41. Tian J Content authentication and recovery using digital watermarks (2008). US Patent 7,389,420

  42. Weng L, Braeckman G, Dooms A, Preneel B, Schelkens P (2012) Robust image content authentication with tamper location. In: Proceedings of ICME’12, pp 380–385. IEEE

  43. Wong PW, Memon N (2001) Secret and public key image watermarking schemes for image authentication and ownership verification. IEEE Trans Image Process 10:1593–1601

    Article  MATH  Google Scholar 

  44. Xie L, Arce GR, Graveman RF (2001) Approximate image message authentication codes. IEEE Trans Multimedia 3(2):242–252

    Article  Google Scholar 

  45. Yeung MM, Mintzer F (1997) An invisible watermarking technique for image verification. In: Proceedings of ICIP’97, vol 2, pp 680–683. IEEE

  46. Zain JM, Fauzi AR (2006) Medical image watermarking with tamper detection and recovery. In: Proceedings of IEEE EMBS’06, pp 3270–3273. IEEE

  47. Zhang Hb, Yang C (2004) Tamper detection and self recovery of images using self-embedding. Chin J Electron 32(2):196–199

    Google Scholar 

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

    Article  Google Scholar 

Download references

Acknowledgments

The assistance of Dr Frank Gaillard (Administrator, Radiopedia, http://radiopaedia.org/) for the test medical images, Professor Anthony Maeder, University of Western Sydney, http://www.uws.edu.au/staff_profiles/uws_profiles/professor_anthony_maeder for making useful suggestions regarding medical image datasets and their web-links, and Dr Beat Schmutz, IHBI, Queensland University of Technology, http://staff.qut.edu.au/staff/schmutz/ for providing MR and CT test images, are noted with gratitude.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering (ECE), Khulna University of Engineering and Technology (KUET), Khulna, 9203, Bangladesh

    Hussain Nyeem

  2. School of Electrical Engineering and Computer Science (EECS), Queensland University of Technology (QUT), Brisbane, QLD 4001, Australia

    Wageeh Boles

  3. Department of Telematics, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway

    Colin Boyd

  4. School of EECS, QUT, Brisbane, QLD 4001, Australia

    Colin Boyd

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  1. Hussain Nyeem
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  2. Wageeh Boles
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Correspondence to Hussain Nyeem.

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Nyeem, H., Boles, W. & Boyd, C. Modelling attacks on self-authentication watermarking. Multimed Tools Appl 75, 15849–15880 (2016). https://doi.org/10.1007/s11042-015-2893-x

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  • DOI: https://doi.org/10.1007/s11042-015-2893-x

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