Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Indonesian Journal of Electrical Engineering and Computer Science
Zied O. Ahmed
Mustansiriyah University

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Biometric key generation using crow algorithm Zied O. Ahmed; Abbas Akram Khorsheed
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp208-214

Abstract

The researchers have been exploring methods to use biometric characteristics of the user as a replacement for using unforgettable pass-word, in an attempt to build robust cryptographic keys, because, human users detect difficulties to call up long cryptographic keys. Biometric recognition provides an authentic solution to the authentication of the user problem in the identity administration systems. With the extensive utilization of biometric methods in different applications, there is growing concern about the confidentiality and security of the biometric technologies. This paper proposes biometric based key recreation scheme. Since human ears are not correlated. Until now, the encryption keys are generated using a swarm intelligence approach. Collective intelligence of simple groups of autonomous agents have been emerged by swarm intelligence. The crow search algorithm which is known as (CSA) is a new meta-intuitive method assembled by the intelligent group behavior of crows. Despite that CSA demonstrates important features, its search approach poses excessive challenges while faced with great multimodal formularization.
Meerkat Clan Algorithm: A New Swarm Intelligence Algorithm Ahmed T. Sadiq Al-Obaidi; Hasanen S. Abdullah; Zied O. Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp354-360

Abstract

Evolutionary computation and swarm intelligence meta-heuristics are exceptional instances that environment has been a never-ending source of creativeness. The behavior of bees, bacteria, glow-worms, fireflies and other beings have stirred swarm intelligence scholars to create innovative optimization algorithms. This paper proposes the Meerkat Clan Algorithm (MCA) that is a novel swarm intelligence algorithm resulting from watchful observation of the Meerkat (Suricata suricatta) in the Kalahari Desert in southern Africa. This animal shows an exceptional intelligence, tactical organizational skills, and remarkable directional cleverness in its traversal of the desert when searching for food. A Meerkat Clan Algorithm (MCA) proposed to solve the optimization problems through reach the optimal solution by efficient way comparing with another swarm intelligence. Traveling Salesman Problem uses as a case study to measure the capacity of the proposed algorithm through comparing its results with another swarm intelligence. MCA shows its capacity to solve the Traveling Salesman’s Problem. Its dived the solutions group to sub-group depend of meerkat behavior that gives a good diversity to reach an optimal solution. Paralleled with the current algorithms for resolving TSP by swarm intelligence, it has been displayed that the size of the resolved problems could be enlarged by adopting the algorithm proposed here.
Co-Authors Abbas Akram Khorsheed Ahmed T. Sadiq Al-Obaidi Hasanen S. Abdullah