IJSEA Volume 5 Issue 3

Improving Security Levels In Automatic Teller Machines (ATM) Using Multifactor Authentication

Frimpong Twum, Kofi Nti, Michael Asante,
10.7753/IJSEA0503.1003
keywords : PIN and Fingerprint-Based; Authentication; Security; Verification; ATM; Verification; Multifactor

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A wide variety of systems need reliable personal recognition system to either authorize or determine the identity of an individual demanding their services. The goal of such system is to warrant that the rendered services are accessed only by a genuine user and no one else. In the absence of robust personal recognition schemes, these systems are vulnerable to the deceits of an imposter. The ATM has suffered a lot over the years against PIN theft and other associated ATM frauds due to its traditional authentication mode (PIN). In this paper, we proposed a multifactor (PIN and Fingerprint) based authentication security arrangement to enhance the security and safety of the ATM and its users. The proposed system demonstrates a three tier design structure. The first tier is the verification module, which concentrates on the enrollment phase, enhancement phase, feature extraction and matching of the fingerprints. The second tier is the database end which acts as a storehouse for storing the fingerprints of all ATM users? preregistered as templates and PIN as text. The last tier presents a system platform to relate banking transactions such as balance inquiries, mini statements and withdrawal. Microsoft windows 8 was used as an operating system platform for the implementation phase, with C# programming language being the front-end development and SQL server 2010 as backend. The application evaluation was based on False Rejection Rate (FAR), False Acceptance Rate (FAR), Average Matching Time (AMT) and the Total Error Rate (TER) conducted, which show the security and reliability of the proposed system for ATM users authentication and verification.
@artical{f532016ijsea05031003,
Title = "Improving Security Levels In Automatic Teller Machines (ATM) Using Multifactor Authentication",
Journal ="International Journal of Science and Engineering Applications (IJSEA)",
Volume = "5",
Issue ="3",
Pages ="126 - 134",
Year = "2016",
Authors ="Frimpong Twum, Kofi Nti, Michael Asante, "}