Emerging Directions in Virtual Worlds and Biometric Security Research

Recent research in the areas of computer graphics, virtual reality and cyberworlds is increasingly concerned with the security applications. In the area of cyberworlds, human features such as faces, hair, walking patterns, voice, behaviour and a manner of communications are being simulated and studied. Moreover, research into social online interactions, and an effort to mimic those interactions and appearances through virtual humans and robots has become abundant. This position paper discusses the state-of-the-art research in the fields of biometric recognition, multi-modal and cancelable biometrics, artificial biometrics and social behavioral studies conducted in the Biometric Technologies laboratory at the University of Calgary, Canada. Social behavioral pattern analysis is the emerging domain in the biometric recognition; the idea behind it is to extract behavioral clues from the everyday human interactions. Activity-related biometric authentication provides an unobtrusive and natural alternative for physiological biometric that can exploit everyday life activities involving interaction with objects or people for extracting biometric signature. Recent research demonstrated that it is possible to extract the behavioral traits not only from traditional behavioral identifiers, such as voice, gait or signature, but also from an online interactions of users or an editing behavior of Wikipedia article authors. An overview of this emerging areas of research that brings virtual worlds modeling and biometric security recognition fields together has been presented at DRDC 2017 National Defense and Security Workshop, Canada. This Editor-in-Chief Position paper is based on the results discussed there as well as on the report submitted to DRDC following the workshop (Gavrilova 2017).