Journal of Intelligent Systems and Internet of Things JISIoT 2690-6791 2769-786X 10.54216/JISIoT https://www.americaspg.com/journals/show/2113 2019 2019 Department of computer sciences, shatt al-arab University college, Al Basrah, 61001, Iraq N. A. Majeed alhammadi Department of computer sciences, shatt al-arab University college, Al Basrah, 61001, Iraq K. Hameed Zaboon Department of computer sciences, shatt al-arab University college, Al Basrah, 61001, Iraq A. Abdulhadi Abdullah The security and privacy fields and multimedia biometrics have been widely used today for personal authentication. Sclera and Palm-print of humans are one of the fastest, accurate, reliable, and secure biometric techniques for identification and verification based on unique features. The majority of the biometric systems are based on the global features, which may lead to weak performance in cases of poor-quality biometric images, therefore, swarm intelligence techniques are used to improve recognition accuracy, reliability, and quickness. In this paper, an enhancement shark smell optimization (ESSO) is proposed to build an efficient hybrid identification system depend on the sclera and palm-print images. The SIFT algorithm used to extract features from the biometric images. The optimal key-points from this feature are obtained using ESSO and chaotic map, and finally, generation digital signature using a 256-MD5 algorithm for each user. The Package of the NIST tests proves that the generated keys are random, unpredictable, uncorrelated, and robust against different kinds of attacks.   2023 2023 21 32 10.54216/JISIoT.100102 https://www.americaspg.com/articleinfo/18/show/2113