الفهرس 
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Abstract
In this thesis, a secure IoT connection between clients and broker server based on iris
recognition system (Authentication Server) is proposed. The trend in this work, is to
use iris as uni-modal biometrics with the aids of multi-biometrics scenarios - other than
the multi-modal - to develop and implement iris-based recognition system.
Regarding to image pre-processing phase, a new algorithm based on masking technique
(MT) to localize iris is proposed. This technique aims to isolate the iris region free of
artifacts without deformation. A modified algorithm based on masking technique
(MMT); to localize iris is proposed. It solves the limitation of the iris data loss,
scalability, and inconsistencies factors, for capturing conditions and different resolution
images. Then, in feature extraction phase, Delta-Mean (DM) and Multi-AlgorithmMean (MAM) - as two new proposed algorithms - are developed to extract iris feature
vectors. In this phase, the fusion between vectors is based on the multi-algorithm
scenario which executed in a parallel processing mode. Fusion for DM and MAM based
features followed by the proposed reduction method reduced the feature vector size
keeping higher performance. Finally, classification is adopted by using Hamming
Distance (HD) and Euclidian Distance (ED) classifiers.
The evaluation of the overall proposed iris system, in verification mode using different
benchmark datasets, gives the convenience of robustness and reliability under different
acquisition factors. Accuracy is over 99.8% with reduction in execution time (about one
second), with minimum possible features. The obtained results show the performance
of the proposed solution for authentication issue. It is suitable for hardware and realtime applications, as it is fast, more accurate, and economic. Thus, It is suitable for
secure MQTT connection message to authenticate right client in sensitive application
over IoT.