AUTHENTICATION SCHEME USING TREE PARITY ARTIFICIAL NEURAL NETWORKS FOR FRAUD DETECTION IN AN ON-LINE BANKING SYSTEM

Hammed, Mudasiru and Adesi, A. B (2019) AUTHENTICATION SCHEME USING TREE PARITY ARTIFICIAL NEURAL NETWORKS FOR FRAUD DETECTION IN AN ON-LINE BANKING SYSTEM. In: 4th National Development Conference of The School of Pure and Applied Science, 2nd – 5th December, 2019, Federal Polytechnic Ilaro, Ogun State.

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Abstract

Internet usage has increased drastically and provides many opportunities such as shopping either online or offline using various facility provided by bank e.g Credit Card, Debit Card, Internet Banking are also possible. But, one of the major problems in the banking is that the way in which adversary and unauthorized users have been gaining access bank resource. However, many studies have proposed numbers method to rapidly detect and identify intrusion in banking transaction.But, unauthorized users are still gaining access to bank resources. This study proposed Tree parity artificial neural network authentication system to detect fraud in banking transaction. The system has been tested with 500student and 450student were successfully login with correct password. But, only 50student were unable to login due to wrong password. This shows that the system is efficient to detect fraud in banking transactions.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Q Science > Q Science (General)
Divisions:	Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User:	Mr Taiwo Egbeyemi
Date Deposited:	02 Sep 2020 09:37
Last Modified:	02 Sep 2020 09:37
URI:	http://eprints.federalpolyilaro.edu.ng/id/eprint/1147

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