A Multi Biometric for Adoptive Key Generation Using Shark Smell Optimization Algorithm

Authors

  • Israa Nazeeh, Jamal Mustafa AL- Tuwaijari

Abstract

Biometric is the measure of behavioral and physiological features for the individual, commonly utilized biometric features for identification or verification, but it is atthe same time can be employed as a key for various security applications. However, the unimodal biometric system is suffering from noise, intraclass variations, non-universality attacks, so to overcome these attacks, the multimodal biometrics system is joining of two or more modalities biometrics. Among various biometric properties like as, fingerprint, face, voice, area, etc., the sclera and palm print biometrics can provide a higher level of security because of its inherent robustness. The main aim of this paper is to design and build a pseudorandom number generator based on the multi-biometric for stream cipher cryptography. The proposed system is based on the use of hybrid biometric identification system that consists of the characteristics of the human sclera and palm print and by using shark smell optimization SSO the proposed system can be found strongest features that used to generate keys with high-quality specifications in terms of unpredictability, randomization, and non-re-generation. The Package of the NIST tests proves that the generated keys are random, unpredictable, uncorrelated, and robust against different kinds of attacks. The multi biometrics keys are enabled of passing most of the NIST statistical tests with high success.

Keywords:Palm Print,Sclera Print,SIFT Algorithm, Shark Smell Optimization SSO algorithm.

Published

2020-07-30

Issue

Section

Articles