Skip to main content

Development of Integrated Distance Authentication and Fingerprint Authorization Mechanism to Reduce Fraudulent Online Transaction

  • Conference paper
  • First Online:
Intelligent Communication, Control and Devices

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 989))

Abstract

From last numerous decades, there is a problem of counterfeit online transaction and posses as a foremost challenge of online transaction. Even though the concrete initiatives have been taken by researchers and governments, fraudsters acquire canny fashion to perform counterfeit online transaction. Fundamentally, fraudster steals the credentials of client and performs counterfeit online transaction. After scrutinizing, this research has stepped forward with a plan to trim down the counterfeit online transaction. This study propounds a working by blending two different workings which are authentication of distance and authorization of fingerprint to execute a genuine transaction. The leading key aspect behind the propound working is that after stealing credentials of the client, fraudsters could not perform counterfeit online transaction. In this study, to assess the impact, propound working is also theoretically implemented in some cases. After the assessment, it is found that the propound working is suitable to prevent counterfeit online transactions.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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. Bhatla, T.P., Prabhu, V., Dua, A.: Understanding credit card frauds. Cards Bus. Rev. 1(6) (2003)

    Google Scholar 

  2. Khattri, V., Singh, D.K.: A Novel Distance Authentication Mechanism to Prevent the Online Transaction Fraud. Advances in Fire and Process Safety, pp. 157–169. Springer, Singapore (2018)

    Google Scholar 

  3. Akole, P., Mane, N., Shinde, K., Swati, A.K.: Secure transactio: an credit card fraud detection system using visual cryptography. Int. Res. J. Eng. Technol. (IRJET). 3(4), 1719–1724 (2016)

    Google Scholar 

  4. Ogbanufe, O., Kim, D.J.: Comparing fingerprint-based biometrics authentication versus traditional authentication methods for e-payment. Decis. Support Syst. 106, 1–14 (2018)

    Article  Google Scholar 

  5. Kulat, A., Kulkarni, R., Bhagwat, N., Desai, K., Kulkarni, M.P.: Prevention of Online transaction frauds using OTP generation based on dual layer security mechanism. Int. Res. J. Eng. Technol. (IRJET). 3(4), 1058–1060 (2016)

    Google Scholar 

  6. Panigrahi, S., Kundu, A., Sural, S., Majumdar, A.K.: Credit card fraud detection: a fusion approach using dempster-shafer theory and bayesian learning. Inf. Fusion. 10(4), 354–363 (2009)

    Article  Google Scholar 

  7. Halvaiee, N.S., Akbari, M.K.: A novel model for credit card fraud detection using Artificial Immune Systems. Appl. Soft Comput. 24, 40–49 (2014)

    Article  Google Scholar 

  8. Soltani, N., Akbari, M.K., Javan, M.S.: A new user-based model for credit card fraud detection based on artificial immune system. In: 16th IEEE CSI International Symposium on Artificial Intelligence and Signal Processing, pp. 029–033 (2012)

    Google Scholar 

  9. Assis, C.A., Pereira,A., Pereira, M.A., Carrano, E.G.: A genetic programming approach for fraud detection in electronic transactions. In: IEEE Symposium on Computational Intelligence in Cyber Security, pp. 1–8 (2014)

    Google Scholar 

  10. RamaKalyani, K., UmaDevi, D.: Fraud detection of credit card payment system by genetic algorithm. Int. J. Sci. Eng. Res. 3(7), 1–6 (2012)

    Google Scholar 

  11. Prakash, A., Chandrasekar, C.: An Optimized multiple semi-hidden Markov model for credit card fraud detection. Indian J. Sci. Technol. 8(2), 165–171 (2015)

    Article  Google Scholar 

  12. Khan, M.Z., Pathan, J.D., Ahmed, A.H.E.: credit card fraud detection system using hidden Markov model and k-clustering. Int. J. Adv. Res. Comput. Commun. Eng. 3(2), 5458–5461 (2014)

    Google Scholar 

  13. Bekirev, A.S., Klimov, V.V., Kuzin, M.V., Shchukin, B.A.: Payment card fraud detection using neural network committee and clustering. Opt. Memory Neural Netw. 24(3), 193–200 (2015)

    Article  Google Scholar 

  14. Van Vlasselaer, V., Bravo, C., Caelen, O., Eliassi-Rad, T., Akoglu, L., Snoeck, M., Baesens, B.: APATE: a novel approach for automated credit card transaction fraud detection using network-based extensions. Decis. Support Syst. 75, 38–48 (2015)

    Article  Google Scholar 

  15. Khan, A.U.S., Akhtar, N., Qureshi, M.N.: Real-Time Credit-Card Fraud Detection using Artificial Neural Network Tuned by Simulated Annealing Algorithm. In: Procedings of International Conference on Recent Trends in Information, Telecommunication and Computing, pp. 113–121 (2014)

    Google Scholar 

  16. Behera, T.K., Panigrahi, S.: Credit card fraud detection: a hybrid approach using fuzzy clustering & neural network. In: Second IEEE International Conference on Advances in Computing and Communication Engineering (ICACCE), pp. 494–499 (2015)

    Google Scholar 

  17. Credit Card and Debit Card Fraud Statistics, https://wallethub.com/edu/credit-debit-card-fraud-statistics/25725/ (2018). Accessed on June 2018

  18. Agoyi, M., Seral, D.: The use of SMS encrypted message to secure automatic teller machine. Proc. Comput. Sci. 3, 1310–1314 (2011)

    Article  Google Scholar 

  19. Sankhwar, S., Pandey, D.: A safeguard against ATM fraud. In: 6th IEEE International Conference on Advanced Computing (IACC), pp. 701–705 (2016)

    Google Scholar 

  20. Nti, I.K., Ansere, J.A., Appiah, A.: Investigating ATM Frauds In Sunyani Municipality: Customer’s Perspective. Int. J. Sci. Eng. Appl. 6(02), 59–65 (2017)

    Google Scholar 

  21. Sakharova, I.: Payment card fraud: Challenges and solutions. In: IEEE International Conference on Intelligence and Security Informatics, pp. 227–234 (2012)

    Google Scholar 

  22. www.eMarketer.com: https://apsalar.com/2016/03/mobile-and-smartphone-usage-statistics-for-india/ (2018). Accessed on June 2018

Download references

Acknowledgements

We extend our gratitude to the Integral University for acknowledging our research work and providing us with Manuscript Communication Number-IU/R&D/2018-MCN000408. We are also indebted to Shri Ramswaroop Memorial University for providing us the financial support for this research work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sandeep Kumar Nayak .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Khattri, V., Nayak, S.K., Singh, D.K. (2020). Development of Integrated Distance Authentication and Fingerprint Authorization Mechanism to Reduce Fraudulent Online Transaction. In: Choudhury, S., Mishra, R., Mishra, R., Kumar, A. (eds) Intelligent Communication, Control and Devices. Advances in Intelligent Systems and Computing, vol 989. Springer, Singapore. https://doi.org/10.1007/978-981-13-8618-3_9

Download citation

Publish with us

Policies and ethics