Cancelable fusion using social network analysis

Authors:
Padma Polash Paul;Marina Gavrilova
Affiliations:
University of Calgary, Calgary, Canada;University of Calgary, Calgary, Canada
Venue:
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Year:
2013

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Abstract

In this paper, novel cancelable biometric template generation algorithm using Social Network Analysis is presented. Two sets of features are fused using Social Network. Proposed fusion technique is cancelable. Eigenvector centrality is used to generate final sets of features from the Virtual Social Network (VSN). The domain transformation of features using VSN confirms the cancelability in biometric template generation.