Skip to main content

Searching Pattern in DNA Sequence Using ECC-Diffie-Hellman Exchange Based Hash Function: An Efficient Approach

  • Conference paper
  • First Online:
Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021) (ICMLBDA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 256))

Included in the following conference series:

Abstract

In this paper, the efficient Elliptic Curve Cryptography with Diffie-Hellman exchange is implemented in order to perform the searching pattern effectively from DNA sequences. The elliptic curve cryptography is defined as public key cryptography which utilizes the elliptic curve properties in terms of finite field. For key exchange process, ECC is combined with Diffie-Hellman algorithm (EC-DH) which is defined as technique for exchanging cryptography keys securely through the public channel. It ensures the security and it highly resistive against the brute force attack. Lesser computational time is obtained and effective security with power consumption achieved. Experimentation results are carried out by using the publicly available dataset. The effectiveness is proved from the comparison results of the proposed and existing study.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
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

Similar content being viewed by others

References

  1. Busia, A., et al.: A deep learning approach to pattern recognition for short DNA sequences. BioRxiv 353474 (2019)

    Google Scholar 

  2. Cherry, K.M., Qian, L.: Scaling up molecular pattern recognition with DNA-based winner take all neural networks. Nature 559, 370–376 (2018)

    Article  Google Scholar 

  3. Kalsi, S., Kaur, H., Chang, V.: DNA cryptography and deep learning using genetic algorithm with NW algorithm for key generation. J. Med. Syst. 42, 1–12 (2018)

    Article  Google Scholar 

  4. Jalali, A., Azarderakhsh, R., Kermani, M.M., Jao, D.: Supersingular isogeny Diffie-Hellman key exchange on 64-bit ARM. IEEE Trans. Depend. Secure Comput. 16, 902–912 (2019)

    Article  Google Scholar 

  5. Mehibel, N., Hamadouche, M.H.: A new approach of elliptic curve Diffie-Hellman key exchange. In: 2017 5th International Conference on Electrical Engineering-Boumerdes (ICEE-B), pp. 1–6 (2017)

    Google Scholar 

  6. Bodur, H., Kara, R.: Implementing Diffie-Hellman key exchange method on logical key hierarchy for secure broadcast transmission. In: 2017 9th International Conference on Computational Intelligence and Communication Networks (CICN), pp. 144–147 (2017)

    Google Scholar 

  7. Xue, X., Zhou, D., Zhou, C.: New insights into the existing image encryption algorithms based on DNA coding. PLoS ONE 15, e0241184 (2020)

    Article  Google Scholar 

  8. Luo, Y., Ouyang, X., Liu, J., Cao, L.: An image encryption method based on elliptic curve elgamal encryption and chaotic systems. IEEE Access 7, 38507–38522 (2019)

    Article  Google Scholar 

  9. Chai, X., Chen, Y., Broyde, L.: A novel chaos-based image encryption algorithm using DNA sequence operations. Opt. Lasers Eng. 88, 197–213 (2017)

    Article  Google Scholar 

  10. Slimane, N.B., Aouf, N., Bouallegue, K., Machhout, M.: An efficient nested chaotic image encryption algorithm based on DNA sequence. Int. J. Mod. Phys. C 29, 1850058 (2018)

    Article  Google Scholar 

  11. Subramanian, E.K., Tamilselvan, L.: Elliptic curve Diffie–Hellman cryptosystem in big data cloud security. Cluster Comput. 23, 3057–3067 (2020)

    Article  Google Scholar 

  12. Norouzi, B., Mirzakuchaki, S.: An image encryption algorithm based on DNA sequence operations and cellular neural network. Multimedia Tools Appl. 76, 13681–13701 (2017)

    Article  Google Scholar 

  13. Neamatollahi, P., Hadi, M., Naghibzadeh, M.: Efficient pattern matching algorithms for DNA sequences. In: 25th International Computer Conference, Computer Society of Iran (CSICC), 2020, pp. 1–6 (2020)

    Google Scholar 

  14. Tahir, M., Sardaraz, M., Ikram, A.A.: EPMA: efficient pattern matching algorithm for DNA sequences. Exp. Syst. Appl. 80, 162–170 (2017)

    Article  Google Scholar 

  15. Fostier, J.: BLAMM: BLAS-based algorithm for finding position weight matrix occurrences in DNA sequences on CPUs and GPUs. BMC Bioinformatics 21, 1–13 (2020)

    Article  Google Scholar 

  16. Ryu, C., Lecroq, T., Park, K.: Fast string matching for DNA sequences. Theoret. Comput. Sci. 812, 137–148 (2020)

    Article  MathSciNet  Google Scholar 

  17. Munirathinam, T., Ganapathy, S., Kannan, A.: Cloud and IoT based privacy preserved e-Healthcare system using secured storage algorithm and deep learning. J. Intell. Fuzzy Syst. 39, 3011–3023 (2020)

    Article  Google Scholar 

  18. Najam, M., Rasool, R.U., Ahmad, H.F., Ashraf, U., Malik, A.W.: Pattern matching for DNA sequencing data using multiple bloom filters. BioMed Res. Int. 2019, 1–9 (2019)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ravikumar, M., Prashanth, M.C., Shivaprasad, B.J. (2022). Searching Pattern in DNA Sequence Using ECC-Diffie-Hellman Exchange Based Hash Function: An Efficient Approach. In: Misra, R., Shyamasundar, R.K., Chaturvedi, A., Omer, R. (eds) Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021). ICMLBDA 2021. Lecture Notes in Networks and Systems, vol 256. Springer, Cham. https://doi.org/10.1007/978-3-030-82469-3_11

Download citation

Publish with us

Policies and ethics