384
Views
7
CrossRef citations to date
0
Altmetric
Articles

Implementation of an Additional Factor for Secure Authentication in Online Transactions

&

References

  • Arthur Williams, D. 2007. Credit card fraud in Trinidad and Tobago. Journal of Financial Crime 14 (3):340–59. doi:10.1108/13590790710758521.
  • Bai, F., and X. Chen. 2013. Analysis on the new types and countermeasures of credit card fraud in mainland China. Journal of Financial Crime 20 (3):267–71. doi:10.1108/JFC-03-2013-0022.
  • Barker, K. J., J. D’amato, and P. Sheridon. 2008. Credit card fraud: Awareness and prevention. Journal of Financial Crime 15 (4):398–410. doi:10.1108/13590790810907236.
  • Bekirev, A. S., V. V. Klimov, M. V. Kuzin, and B. A. Shchukin. 2015. Payment card fraud detection using neural network committee and clustering. Optical Memory and Neural Networks 24 (3):193–200. doi:10.3103/S1060992X15030030.
  • Ben-Asher, N., and C. Gonzalez. 2015. Effects of cyber security knowledge on attack detection. Computers in Human Behavior 48:51–61. doi:10.1016/j.chb.2015.01.039.
  • Bhatla, T. P., V. Prabhu, and A. Dua. 2003. Understanding credit card frauds. Cards business review. Accessed January 15, 2018. https://popcenter.asu.edu/sites/default/files/problems/credit_card_fraud/PDFs/Bhatla.pdf.
  • Bürk, H., and A. Pfitzmann. 1989. Digital payment systems enabling security and unobservability. Computers & Security 8 (5):399–416. doi:10.1016/0167-4048(89)90022-9.
  • Carneiro, E. M., L. A. V. Dias, A. M. da Cunha, and L. F. S. Mialaret. 2015. Cluster analysis and artificial neural networks: A case study in credit card fraud detection. Proceeding of the ITNG 2015 Conference on Information Technology-New Generations, IEEE, 122–26. doi:10.1109/ITNG.2015.25.
  • Changchit, C., R. Lonkani, and J. Sampet. 2017. Mobile banking: Exploring determinants of its adoption. Journal of Organizational Computing and Electronic Commerce 27 (3):239–61. doi:10.1080/10919392.2017.1332145.
  • Dasgupta, D., A. Roy, and A. Nag. 2017. Multi-factor authentication. In Advances in user authentication. Infosys science foundation series, 185–233. Cham: Springer. doi:10.1007/978-3-319-58808-7_5.
  • Dasgupta, D., S. Yu, and N. S. Majumdar. 2003. MILA—Multilevel immune learning algorithm. Proceedings of Conference on Genetic and Evolutionary Computation, Springer, 183–94. doi: 10.1007/3-540-45105-6_24.
  • Gardiner, B. 2010. How anyone can fake an ATM and steal your money. Accessed April 16, 2018. https://gizmodo.com/5687689/how-anyone-can-fake-an-atm-and-steal-your-money.
  • Gunson, N., D. Marshall, H. Morton, and M. Jack. 2011. User perceptions of security and usability of single-factor and two-factor authentication in automated telephone banking. Computers & Security 30 (4):208–20. doi:10.1016/j.cose.2010.12.001.
  • Halvaiee, N. S., and M. K. Akbari. 2014. A novel model for credit card fraud detection using Artificial Immune Systems. Applied Soft Computing 24:40–49. doi:10.1016/j.asoc.2014.06.042.
  • Hinde, S. 2002. Spam, scams, chains, hoaxes and other junk mail. Computers & Security 21 (7):592–606. doi:10.1016/S0167-4048(02)01104-5.
  • Kabanda, S., M. Tanner, and C. Kent. 2018. Exploring SME cybersecurity practices in developing countries. Journal of Organizational Computing and Electronic Commerce 28 (3):269–82. doi:10.1080/10919392.2018.1484598.
  • Kaur, P., K. Krishan, S. K. Sharma, and T. Kanchan. 2018. ATM card cloning and ethical considerations. Science and Engineering Ethics 1–10. doi:10.1007/s11948-018-0049-x.
  • Kennedy, E., and C. Millard. 2016. Data security and multi-factor authentication: Analysis of requirements under EU law and in selected EU Member States. Computer Law & Security Review 32 (1):91–110. doi:10.1016/j.clsr.2015.12.004.
  • Khattri, V., and D. K. Singh. 2018. A novel distance authentication mechanism to prevent the online transaction fraud. In Advances in fire and process safety. Springer transactions in civil and environmental engineering, ed. N. Siddiqui, S. Tauseef, S. Abbasi, and A. Rangwala. 157–69. Singapore: Springer. doi:10.1007/978-981-10-7281-9_13.
  • Kiernan, J. S. 2016. Credit card & debit card fraud statistics. Accessed June 20, 2018. https://wallethub.com/edu/credit-debit-card-fraud-statistics/25725/.
  • Laux, D., A. Luse, B. Mennecke, and A. M. Townsend. 2011. Adoption of biometric authentication systems: Implications for research and practice in the deployment of end-user security systems. Journal of Organizational Computing and Electronic Commerce 21 (3):221–45. doi:10.1080/10919392.2011.590111.
  • Ometov, A., S. Bezzateev, N. Mäkitalo, S. Andreev, T. Mikkonen, and Y. Koucheryavy. 2018. Multi-factor authentication: A survey. Cryptography 2 (1):1–31. doi:10.3390/cryptography2010001.
  • Pearce, M., S. Zeadally, and R. Hunt. 2010. Assessing and improving authentication confidence management. Information Management & Computer Security 18 (2):124–39. doi:10.1108/09685221011048355.
  • Sankhwar, S., and D. Pandey. 2016. A safeguard against ATM fraud. Proceedings of IEEE 2016 Conference on Advanced Computing (IACC), Bhimavaram, India, 701–05. doi: 10.1109/IACC.2016.135.
  • San-Martín, S., and C. Camarero. 2012. A cross-national study on online consumer perceptions, trust, and loyalty. Journal of Organizational Computing and Electronic Commerce 22 (1):64–86. doi:10.1080/10919392.2012.642763.
  • Soltani, N., M. K. Akbari, and M. S. Javan. 2012. A new user-based model for credit card fraud detection based on artificial immune system. Proceedings of AISP 2012 Conference on Artificial Intelligence and Signal Processing, IEEE, 29–33. doi:10.1109/AISP.2012.6313712.
  • Vardhani, P. R., Y. I. Priyadarshini, and Y. Narasimhulu. 2019. CNN data mining algorithm for detecting credit card fraud. In Soft computing and medical bioinformatics. springer briefs in applied sciences and technology, 85–93. Singapore: Springer. doi:10.1007/978-981-13-0059-2_10.
  • Von Solms, R., and J. Van Niekerk. 2013. From information security to cyber security. Computers & Security 38:97–102. doi:10.1016/j.cose.2013.04.004.
  • Weir, C. S., G. Douglas, M. Carruthers, and M. Jack. 2009. User perceptions of security, convenience and usability for ebanking authentication tokens. Computers & Security 28 (1–2):47–62. doi:10.1016/j.cose.2008.09.008.
  • West, J., and M. Bhattacharya. 2016. Intelligent financial fraud detection: A comprehensive review. Computers & Security 57:47–66. doi:10.1016/j.cose.2015.09.005.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.