الفهرس 
Chapter 1: IntroductionOnly 14 pages are availabe for public view
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Abstract
This thesis is concerned with a vital topic in securing communication
networks. Our main concern is how to access the networks. Security tools
are needed for this task. It can be implemented via a biometric verification
system. The utilization of open biometrics in public databases is not
recommended. Hence, there is a need to use cancellable biometric systems.
This thesis presents an elegant form for generating cancelable biometric
templates through including some intended distortion in biometric
templates to keep the original ones away from hacking attempts. This
objective is achieved with the help of adaptive filtering algorithms and
quaternion mathematics. Moreover, optimization tools are also used to
obtain the best biometric system performance. Two adaptive filter
algorithms are utilized in this thesis to generate the cancellable biometric
templates. They are the Least Mean Square (LMS) algorithm, and the Leaky
Least Mean Square (LLMS) algorithm. The main idea is to use the
biometric template as an input to the adaptive filter with an arbitrary desired
response. Hence, the cancelable biometric template is extracted from the
weights of the filter as a signature for the original template. All adaptive
filters used are built with quaternion mathematics. Whale optimization is
used to select the best value for the weights used in the LLMS algorithm. A
comparison study is presented between the results of the proposed
algorithms and those obtained with an ordinary implementation of
quaternion mathematics for cancelable biometrics. Simulation results prove
that the cancelable biometric system based on the LLMS algorithm and
quaternion mathematics with optimization achieves the best performance.