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Cancelable Biometrics Using Deep Learning as a Cloud Service

Tanuja Sudhakar, Marina L. Gavrilova

2020IEEE Access35 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

BiometricsCloud computingComputer scienceScalabilityPopularitySoftware deploymentComputer securityAuthentication (law)Service (business)Deep learningArtificial intelligenceDistributed computingDatabaseSoftware engineeringOperating systemSocial psychologyEconomyPsychologyEconomicsBiometric Identification and SecurityUser Authentication and Security SystemsAdvanced Steganography and Watermarking Techniques
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