Cancelable Biometrics Using Deep Learning as a Cloud Service

被引:15
|
作者
Sudhakar, Tanuja [1 ]
Gavrilova, Marina [1 ]
机构
[1] Univ Calgary, Dept Comp Sci, Calgary, AB T2N 1N4, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Biometric privacy; cloud computing; cancelable biometrics; deep learning;
D O I
10.1109/ACCESS.2020.3003869
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud computing is a technology that has gained rapid popularity in recent years. It has enabled use of immense computational power in a scalable and cost-efficient manner. Deployment of biometric technology in government and commercial organizations has become a standard security practice. However, independent biometric systems tend to be computationally and financially expensive, especially when user enrollment is high. A feasible solution is to create a biometric system on the cloud which can be used ubiquitously as an authentication service. In this paper, we propose a first cancelable biometric framework based on deep learning on the cloud. We establish that cloud is a good solution for biometric systems where intensive computation, quick response times, and high accuracy is required.
引用
收藏
页码:112932 / 112943
页数:12
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