Gavrilova, MarinaTumpa, Sanjida Nasreen2022-05-022022-05-022022-04Tumpa, 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.http://hdl.handle.net/1880/114590Online 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.engUniversity 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.Social Behavioral BiometricsOnline Social NetworkUser IdentificationCyber SecurityComputer Sciencemaster thesis10.11575/PRISM/39710