Online User Recognition using Social Behavioral Biometric System

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dc.contributor.advisorGavrilova, Marina
dc.contributor.authorTumpa, Sanjida Nasreen
dc.contributor.committeememberZhao, Richard
dc.contributor.committeememberUllyot, Michael
dc.date2022-06
dc.date.accessioned2022-05-02T15:48:56Z
dc.date.available2022-05-02T15:48:56Z
dc.date.issued2022-04
dc.description.abstractOnline Social Networking (OSN) platforms have become an integral part of the daily life of individuals around the world. The uniqueness of social interactions on online social networks draws the attention of cybersecurity research. Social Behavioral Biometric (SBB) systems extract unique patterns from online communication trails and generate digital fingerprints for user identification. This research investigates the impact of users’ vocabulary to conclude whether such features contribute to user authentication. This thesis combines for the first time the textual, contextual and interpersonal communicative information of users in online social networks to develop a social behavioral biometric system. This thesis also pioneers the comparative study of fusion methods in SBB systems. The proposed system achieves 99.25% recognition accuracy and outperforms all prior research on SBB. In addition, the effects of template aging on the individual SBB traits and the overall system have been analyzed first-ever. The experimental results on permanence evaluation demonstrate that the developed system can perform remarkably well despite the template aging effect.en_US
dc.identifier.citationTumpa, S. N. (2022). Online user recognition using social behavioral biometric system (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/39710
dc.identifier.urihttp://hdl.handle.net/1880/114590
dc.language.isoengen_US
dc.publisher.facultySchulich School of Engineeringen_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.subjectSocial Behavioral Biometricsen_US
dc.subjectOnline Social Networken_US
dc.subjectUser Identificationen_US
dc.subjectCyber Securityen_US
dc.subject.classificationComputer Scienceen_US
dc.titleOnline User Recognition using Social Behavioral Biometric Systemen_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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