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Paper Document Authentication Using Print-Scan Resistant Image Hashing and Public-Key Cryptography

  • Fawad AhmadEmail author
  • Lee-Ming Cheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11611)

Abstract

Identity documents, such as passports, visa stickers, national identity cards and educational institutions’ identity cards etc., are used for personal identity verification by different government and academic organizations. These printed domain documents can be counterfeited by deploying different forgery techniques. This work suggests authenticity verification of printed documents and their sources using digital signature based on print-scan resistant image hashing and public-key cryptography. We present application of print-scan resistant image hashing based on wave atom transform (WAT) for document authentication. Image hash is calculated by extracting robust image features in WAT domain. Hash value of the person’s original image is encrypted with the private key of trusted authorities to form a digital signature which is encoded in a QR code printed on the document. Digital signature, extracted from a QR code, is decrypted with the public key of trusted authorities for identity verification, thus provides offline verification of printed documents without the need of online network access or database.

Keywords

Document authentication Document security Image hashing Print-scan process Wave atom transform Public-key cryptography 

References

  1. 1.
    Ahmed, A.G.H., Shafait, F.: Forgery detection based on intrinsic document contents. In: 2014 11th IAPR International Workshop on Document Analysis Systems (DAS), pp. 252–256. IEEE (2014)Google Scholar
  2. 2.
    Eskenazi, S., Bodin, B., Gomez-Krämer, P., Ogier, J.M.: A perceptual image hashing algorithm for hybrid document security. In: 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), vol. 1, pp. 741–746. IEEE (2017)Google Scholar
  3. 3.
    Warasart, M., Kuacharoen, P.: Paper-based document authentication using digital signature and QR code. In: 4th International Conference on Computer Engineering and Technology, pp. 94–98 (2012)Google Scholar
  4. 4.
    Ambadiyil, S., Vibhath, V.B., Mahadevan Pillai, V.P.: On Paper Digital Signature (OPDS). In: Advances in Signal Processing and Intelligent Recognition Systems. AISC, vol. 425, pp. 547–558. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-28658-7_46Google Scholar
  5. 5.
    Ambadiyil, S., Vibhath, V. B., Pillai, V.M.: Performance analysis and security dependence of on paper digital signature using random and critical content. In: 2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), pp. 722–725. IEEE (2016)Google Scholar
  6. 6.
    Ahmad, F., Cheng, L.-M, Khan, A.: Lightweight and privacy-preserving template generation for palm-vein based human recognition. IEEE Trans. Inf. Forensics Secur. (2019).  https://doi.org/10.1109/tifs.2019.2917156
  7. 7.
    Ahmad, F., Cheng, L.-M.: Authenticity and copyright verification of printed images. Sig. Process. 148, 322–335 (2018)CrossRefGoogle Scholar
  8. 8.
    Sharma, G.: Image-based data interfaces revisited: barcodes and watermarks for the mobile and digital worlds. In: 2016 8th International Conference on Communication Systems and Networks (COMSNETS), pp. 1–6. IEEE (2016)Google Scholar
  9. 9.
    Ahmad, F., Cheng, L.-M.: Watermark extraction under print-cam process using wave atoms based blind digital watermarking. In: Proceedings of the 2nd International Conference on Vision, Image and Signal Processing, p. 59. ACM (2018)Google Scholar
  10. 10.
    Li, C.M., Hu, P., Lau, W.C.: AuthPaper: protecting paper-based documents and credentials using authenticated 2D barcodes. In: 2015 IEEE International Conference on Communications (ICC), pp. 7400–7406. IEEE (2015)Google Scholar
  11. 11.
    Klein, D., Kruse, J.: A comparative study on image hashing for document authentication. In: 2015 International Conference of the Biometrics Special Interest Group (BIOSIG), pp. 1–5. IEEE (2015)Google Scholar
  12. 12.
    Demanet, L., Ying, L.: Wave atoms and sparsity of oscillatory patterns. Appl. Comput. Harmonic Anal. 23, 368–387 (2007)MathSciNetCrossRefGoogle Scholar
  13. 13.
    FEI face database. https://fei.edu.br/~cet/facedatabase.html. Accessed 28 Feb 2019

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Electronic EngineeringCity University of Hong KongKowloonHong Kong

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