Author
Abhilasha Bhargav-Spantzel, Elisa Bertino, Anna Squicciarini, Xiangwei Kong, Weike Zhang
Abstract
We present algorithms to reliably generate biometric
identifiers from a user's biometric image which in turn is used
for identity verification possibly in conjunction with
cryptographic keys. The biometric identifier generation
algorithms employ image hashing functions using singular value
decomposition and support vector classification techniques. Our
algorithms capture generic biometric features that ensure
unique and repeatable biometric identifiers. We provide an
empirical evaluation of our techniques using 2569 images of 488
different individuals for three types of biometric images;
namely fingerprint, iris and face. Based on the biometric type
and the classification models, as a result of the empirical
evaluation we can generate biometric identifiers ranging from
64 bits up to 214 bits. We provide an example use of the
biometric identifiers in privacy preserving multi-factor
identity verification based on zero knowledge proofs. Therefore
several identity verification factors, including various
traditional identity attributes, can be used in conjunction
with one or more biometrics of the individual to provide strong
identity verification. We also ensure security and privacy of
the biometric data. More specifically, we analyze several
attack scenarios. We assure privacy of the biometric using the
one-way hashing property, in that no information about the
original biometric image is revealed from the biometric
identifier.