Voice-based Dynamic Time Warping Recognition Scheme for Enhanced Database Access Security
DOI:
https://doi.org/10.59247/jfsc.v3i1.293Keywords:
Time-warping, Voice-based Biometrics, Convolution Neural NetworkAbstract
Rapid transformation with database security has remained imperative as unauthorized access exposes sensitive data to adversaries. To curb this, we suggest using a secured dynamic time-warp scheme to improve access to the database schemas. The study integrates voice biometrics with two-factor authentication to yield a robust, user-friendly platform, which utilizes time-warping to authenticate voice patterns against the variability in utterance speed. Results showcase high accuracy and resiliency in its usage against spoofing attacks as compared to state-of-the-art voice recognition systems. The model ensures the minimal possibility of credential theft by binding the access of databases to the voice features of authorized users. The study shows the system's architecture, implementation, and performance evaluation, highlighting its potential to revolutionize database security in various applications. The findings underscore the importance of leveraging advanced biometric techniques to safeguard critical information systems.
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Copyright (c) 2024 Paul Avweresuo Onoma, Eferhire Valentine Ugbotu, Tabitha Chukwudi Aghaunor, Joy Agboi, Arnold Adimabua Ojugo, Christopher Chukwufunaya Odiakaose, Asuobite ThankGod Max-Egba, Star Umiyemeromesu Niemogha, Amaka Patience Binitie, Mustapha Barau Abdullahi
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