Skip to main content
SpringerLink
Log in

Efficient Image Authentication Scheme Using Genetic Algorithms

  • Conference paper
  • First Online:
Distributed Computing and Internet Technology (ICDCIT 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10109))

  • 753 Accesses

Abstract

We present an efficient image authentication scheme using Genetic algorithm (GA). Using the crossover and mutation process of GA the original image is randomized into a binary string. A pairing function is then used as a checksum function that converts the binary string to a fixed length digest of the original image. A random permutation is used as the secret parameter between the authenticator generator and verifier. The scheme provides a non-reversible compression and collision resistance property, and is secure against chosen plaintext attacks. The experimental results show that the proposed scheme is efficient in comparisons to standard cryptographic authentication algorithms.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Furht, B., Kirovski, D.: Multimedia Security Handbook. CRC Press, Boca Raton (2004)

    Book  Google Scholar 

  2. Wan, R.Z., Lin, C.F., Lin, J.C.: Image hiding by optimal LSB substitution and genetic algorithm. Pattern Recogn. 34(3), 671–683 (2001)

    Article  MATH  Google Scholar 

  3. Afarin, R., Mozaffari, S.: Image encryption using genetic algorithm. In: proceedings of the Conference of Machine Vision and Image Processing, pp. 441–445 (2013)

    Google Scholar 

  4. Khodaei, M., Faez, K.: Image hiding by using genetic algorithm and LSB substitution. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D., Meunier, J. (eds.) ICISP 2010. LNCS, vol. 6134, pp. 404–411. Springer, Heidelberg (2010). doi:10.1007/978-3-642-13681-8_47

    Chapter  Google Scholar 

  5. Wang, X., Pang, K., Zhou, X., Zhou, Y.: A visual model-based perceptual image hash for content authentication. IEEE Trans. Inf. Forensics Secur. 10(7), 1336–1349 (2014)

    Article  Google Scholar 

  6. Liu, F., Wang, H., Cheng, L.-M., Ho, A.T.S., Li, S.: Enhanced perceptual image authentication with tamper localization and self-restoration. In proceedings of IEEE International Conference on Multimedia and Expo, pp. 1–6 (2014)

    Google Scholar 

  7. Monga, V., Mhcak, M.K.: Robust and secure image hashing via non-negative matrix factorizations. IEEE Trans. Inf. Forensics Secur. 2(3), 376–390 (2007)

    Article  Google Scholar 

  8. Swaminathan, A., Mao, Y., Wu, M.: Robust and secure image hashing. IEEE Trans. Inf. Forensics Secur. 1(2), 215–230 (2006)

    Article  Google Scholar 

  9. Enayatifar, R., Abdullah,A.H.: Image security via genetic algorithm. In: proceedings of International Conference on Computer and Software Modeling, pp. 198–203 (2011)

    Google Scholar 

  10. Ismail, I.A., Amin, M., Diab, H.: A digital image encryption algorithm based a composition of two chaotic logistic maps. Int. J. Netw. Secur. 11(1), 1–10 (2010)

    Google Scholar 

  11. Chang, C.C., Hu, Y.S., Lu, T.C.: A watermarking-based image ownership and tampering authentication scheme. Pattern Recogn. Lett. 27(5), 439–446 (2006)

    Article  Google Scholar 

  12. Ahmed, F., Siyal, M.Y., Abbas, V.U.: A secure and robust hash-based scheme for image authentication. J. Signal Process. 90(5), 1456–1470 (2010)

    Article  MATH  Google Scholar 

  13. Vanstone, S., van Oorschot, P., Menezes, A.: Handbook of Applied Cryptography. CRC Press, Boca Raton (1996)

    MATH  Google Scholar 

  14. Tang, Y.L., Hwang, M.S., Yang, C.R.: An image authentication scheme based on digital signatures. Pak. J. Appl. Sci. 2(5), 553–557 (2002)

    Article  Google Scholar 

  15. Holland, J.H.: Genetic algorithms. Sci. Am., 66–72 (1992)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. DA-IICT, Gandhinagar, India

    Arjun Londhey & Manik Lal Das

Authors
  1. Arjun Londhey
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manik Lal Das
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Manik Lal Das .

Editor information

Editors and Affiliations

  1. Oracle Labs, Brisbane, Queensland, Australia

    Padmanabhan Krishnan

  2. Infosys Limited, Hyderabad, India

    P. Radha Krishna

  3. IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA

    Laxmi Parida

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Londhey, A., Das, M.L. (2017). Efficient Image Authentication Scheme Using Genetic Algorithms. In: Krishnan, P., Radha Krishna, P., Parida, L. (eds) Distributed Computing and Internet Technology. ICDCIT 2017. Lecture Notes in Computer Science(), vol 10109. Springer, Cham. https://doi.org/10.1007/978-3-319-50472-8_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-50472-8_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50471-1

  • Online ISBN: 978-3-319-50472-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation