Cancelable Biometric System Based on Deep Learning

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dc.contributor.advisorGavrilova, Marina L.
dc.contributor.authorSudhakar, Tanuja
dc.contributor.committeememberJacob, Christian P.
dc.contributor.committeememberHenry, Ryan
dc.contributor.committeememberGavrilova, Marina L.
dc.date2020-11
dc.date.accessioned2020-09-29T13:08:06Z
dc.date.available2020-09-29T13:08:06Z
dc.date.issued2020-09-24
dc.description.abstractWith the increasing number of cyberattacks, Personal Identification Numbers (PINs), tokens, and passwords have been found to be insufficient for identity protection. Over the past decade, biometric systems have gained high popularity in providing secure mechanisms for user authentication. In this thesis, the safety of biometric data is rendered through the technique of ‘Cancelable Biometrics’. A cancelable biometric system for multi-instance biometrics has been designed with the use of deep learning. A deep learning architecture based on Convolutional Neural Network (CNN) and Multi Layer Perceptron (MLP) is presented to create a novel, accurate, and secure cancelable biometric solution. An implementation of the proposed solution has also been carried out on the cloud platform to provide a ubiquitous cancelable biometric authentication service. A high authentication accuracy, biometric template security and cancelability, fast response times, and cost efficiency are the merits of the presented cancelable biometric system.en_US
dc.identifier.citationSudhakar, T. (2020). Cancelable Biometric System Based on Deep Learning (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/38262
dc.identifier.urihttp://hdl.handle.net/1880/112603
dc.language.isoengen_US
dc.publisher.facultyScienceen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectBiometricsen_US
dc.subjectCancelable biometricsen_US
dc.subjectDeep learningen_US
dc.subjectClouden_US
dc.subjectBiometric securityen_US
dc.subjectMachine learningen_US
dc.subject.classificationEducation--Sciencesen_US
dc.subject.classificationComputer Scienceen_US
dc.titleCancelable Biometric System Based on Deep Learningen_US
dc.typemaster thesisen_US
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameMaster of Science (MSc)en_US
ucalgary.item.requestcopytrueen_US
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