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Hybrid Model for Online Payment Syetem with Object-Oriented Methodology

Amanze 1 , B.C. 2 , Okoronkwo 3 , M.C. 4 , Chilaka 5 , U.L 6

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-4 , Page no. 374-385, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i4.374385

Online published on Apr 30, 2019

Copyright © Amanze, B.C., Okoronkwo, M.C., Chilaka, U.L . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Amanze, B.C., Okoronkwo, M.C., Chilaka, U.L, “Hybrid Model for Online Payment Syetem with Object-Oriented Methodology,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.374-385, 2019.

MLA Style Citation: Amanze, B.C., Okoronkwo, M.C., Chilaka, U.L "Hybrid Model for Online Payment Syetem with Object-Oriented Methodology." International Journal of Computer Sciences and Engineering 7.4 (2019): 374-385.

APA Style Citation: Amanze, B.C., Okoronkwo, M.C., Chilaka, U.L, (2019). Hybrid Model for Online Payment Syetem with Object-Oriented Methodology. International Journal of Computer Sciences and Engineering, 7(4), 374-385.

BibTex Style Citation:
@article{_2019,
author = {Amanze, B.C., Okoronkwo, M.C., Chilaka, U.L},
title = {Hybrid Model for Online Payment Syetem with Object-Oriented Methodology},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {7},
Issue = {4},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {374-385},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4046},
doi = {https://doi.org/10.26438/ijcse/v7i4.374385}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i4.374385}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4046
TI - Hybrid Model for Online Payment Syetem with Object-Oriented Methodology
T2 - International Journal of Computer Sciences and Engineering
AU - Amanze, B.C., Okoronkwo, M.C., Chilaka, U.L
PY - 2019
DA - 2019/04/30
PB - IJCSE, Indore, INDIA
SP - 374-385
IS - 4
VL - 7
SN - 2347-2693
ER -

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Abstract

The business-to-consumer aspect of electronic commerce (e-commerce) is the most visible business use of the World Wide Web. The primary goal of an e-commerce site is to sell goods and services online with security of customers’ giving optimum consideration. This paper deals with development of fraud detection and alerting system using Hidden Markov Model and Artificial Neural Network. The system is implemented using a 3-tier approach, with a backend database, a middle tier of WAMP Server, and a web browser as the front end client. In order to finalize payment of goods, the customer must authenticate this approach through Code and OTP match. Whereby the authentication process fails, the transaction would not be completed and real-time alert would be sent to both the e-commerce system and payment system. This will enable their (e-commerce and payment system) platform to electronically deactivate the victims’ account.

Key-Words / Index Term

ANN, HMM, e-Commerce and Payment System

References

[1] Vasarhelyi, M.A. (2010): ‘Expert System in Accounting and Auditing/f Artificial Intelligence in Accounting and Auditing.
[2]Bhatla, T. P. (2013): “Understanding Credit Card Frauds” Card business review. http://www.tcs.com/0_whitepapers/htdocs/credit_card_fraud_white_paper_V_1.0.pdf.
[3] Hassler, V. (2011): “Security Fundamentals for E-commerce”, computer security series.
[4] Tae-Hwan, S., Paula, S. (2008): “Identifying Effectiveness Criteria for Internet Payment Systems”, A Journal of Internet Research: Networking Applications and Policy, v-8 number 3, pp 202-218.
[5] Edwards.com
[6] Creditcard.com
[7] Kovach, S and Ruggiero, W. V. (2011): “Online Banking Fraud Detection Based on Local and Global Behavior” ICDS 2011: The Fifth International Conference on Digital Society.
[8] Kappelin, F. and Rudvall, J. (2015): “Fraud Detection within Mobile Money: A mathematical statistics approach” MSc Thesis submitted to the Dept. Computer Science & Engineering Blekinge Institute of Technology SE–371 79 Karlskrona, Sweden.
[9] Chen, M., Han, J. and Yu, P. S. (2012) “Data mining: An Overview from a Database Perspective,” IEEE Transactions on Knowledge and Data Engineering, vol. 8, no. 6, pp. 866-883.
[10] Ngai, E., Hu, Y., Wong, Y., Chen, Y. and Sun, X. (2011): “The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature,” Decision Support Systems, pp. 559-569, 2011.
[11] Meyer, D. (2012): “Support Vector Machines,” Technische Universit¨at Wien,, Austria, 2012.