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Fingereye: improvising security and optimizing ATM transaction time based on iris-scan authentication

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 9 No. 3 (2019)

DOI
10.11591/ijece.v9i3.pp1879-1886
ISSN
2088-8708, 2088-8708
Published
2019-06-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

The tumultuous increase in ATM attacks using eavesdropping, shoulder-surfing, has risen great concerns. Attackers often target the authentication stage where a customer may be entering his login information on the ATM and thus use direct observation techniques by looking over the customer's shoulder to steal his passwords. Existing authentication mechanism employs the traditional password-based authentication system which fails to curb these attacks. This paper addresses this problem using the FingerEye. The FingerEye is a robust system integrated with iris-scan authentication. A customer’s profile is created at registration where the pattern in his iris is analyzed and converted into binary codes. The binary codes are then stored in the bank database and are required for verification prior to any transaction. We leverage on the iris because every user has unique eyes which do not change until death and even a blind person with iris can be authenticated too. We implemented and tested the proposed system using CIMB bank, Malaysia as case study. The FingerEye is integrated with the current infrastructure employed by the bank and as such, no extra cost was incurred. Our result demonstrates that ATM attacks become impractical. Moreover, transactions were executed faster from 6.5 seconds to 1.4 seconds.

Collaboration network of the authors

5 authors · 10 co-authorship links · 4 across different organisations

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  • Universiti Sains Malaysia
  • Islamia University of Bahawalpur
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Fingereye: improvising security and optimizing ATM transaction time based on iris-scan authentication</dc:title><dc:creator>Omolara, Abiodun Esther</dc:creator><dc:creator>Jantan, Aman</dc:creator><dc:creator>Abiodun, Oludare Isaac</dc:creator><dc:creator>Arshad, Humaira</dc:creator><dc:creator>Mohamed, Nachaat AbdElatif</dc:creator><dc:description>&lt;jats:p&gt;The tumultuous increase in ATM attacks using eavesdropping, shoulder-surfing, has risen great concerns. Attackers often target the authentication stage where a customer may be entering his login information on the ATM and thus use direct observation techniques by looking over the customer's shoulder to steal his passwords. Existing authentication mechanism employs the traditional password-based authentication system which fails to curb these attacks. This paper addresses this problem using the FingerEye. The FingerEye is a robust system integrated with iris-scan authentication. A customer’s profile is created at registration where the pattern in his iris is analyzed and converted into binary codes. The binary codes are then stored in the bank database and are required for verification prior to any transaction. We leverage on the iris because every user has unique eyes which do not change until death and even a blind person with iris can be authenticated too. We implemented and tested the proposed system using CIMB bank, Malaysia as case study. The FingerEye is integrated with the current infrastructure employed by the bank and as such, no extra cost was incurred. Our result demonstrates that ATM attacks become impractical. Moreover, transactions were executed faster from 6.5 seconds to 1.4 seconds.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2019-06-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v9i3.pp1879-1886</dc:identifier><dc:identifier>10.11591/ijece.v9i3.pp1879-1886</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 9 No 3 (2019); 1879</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/13619/12037</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>