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  • On reinforcing automatic teller machine (ATM) transaction authentication security process by imposing behavioral biometrics

    Author(s)
    Mondal, Prakash Chandra
    Deb, Rupam
    Adnan, Md. Nasim
    Griffith University Author(s)
    Deb, Rupam
    Year published
    2017
    Metadata
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    Abstract
    Automatic Teller Machine (ATM) is popular to the bank customers since it can dispense cash quickly with high availability in most of the places alongside the street or in the bank premise. Customers are not bound to carry cash for its constant service and location independence (almost everywhere). Nowadays, ATM is under threat by fraudsters like card skimming, salisi gang, cash trapping, fake assistance, shoulder surfing, eavesdropping, fake PIN pad overlay, hold-ups etc. In various methods of ATM transaction processes, physical biometric identification and token based three factor authentications are required to capture ...
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    Automatic Teller Machine (ATM) is popular to the bank customers since it can dispense cash quickly with high availability in most of the places alongside the street or in the bank premise. Customers are not bound to carry cash for its constant service and location independence (almost everywhere). Nowadays, ATM is under threat by fraudsters like card skimming, salisi gang, cash trapping, fake assistance, shoulder surfing, eavesdropping, fake PIN pad overlay, hold-ups etc. In various methods of ATM transaction processes, physical biometric identification and token based three factor authentications are required to capture original information from the customers and new identification device is needed to install although those are costly. This paper proposes new methods of three factor authentications using online handwriting signature verification from customer account profile database along with chip based card and PIN after considering cost involvement, effectiveness and installation viability. These methods of authentication will not require further enhancement of bank's database with new credential data like physical biometrics information (iris pattern, finger print, speech, face images, etc.).
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    Conference Title
    Proceedings of the 2017 4th International Conference on Advances in Electrical Engineering (ICAEE)
    DOI
    https://doi.org/10.1109/ICAEE.2017.8255383
    Subject
    Electrical and Electronic Engineering not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/377061
    Collection
    • Conference outputs

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