Exploiting an Elitist Barnacles Mating Optimizer implementation for substitution box optimization
Kamal Z. Zamli,
Fakhrud Din,
Hussam S. Alhadawi,
Shah Khalid,
Hadeel Alsolai,
Mohamed K. Nour,
Fahd N. Al-Wesabi,
Muhammad Assam
Affiliations
Kamal Z. Zamli
Faculty of Computing, Universiti Malaysia Pahang, Pekan, Malaysia; Faculty of Science and Technology, Universitas Airlangga, C Campus JI. Dr. H. Soekamo, Mulyorejo, Surabaya 60115, Indonesia
Fakhrud Din
Faculty of Information Technology, University of Malakand, KPK, Pakistan
Hussam S. Alhadawi
Computers Technologies Engineering Department, Dijlah University College, Baghdad, Iraq; College of Engineering, University of Warith Al-Anbiyaa, Karbala, Iraq
Shah Khalid
Faculty of Information Technology, University of Malakand, KPK, Pakistan
Hadeel Alsolai
Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
Mohamed K. Nour
Department of Computer Sciences, College of Computing and Information System, Umm Al-Qura University, Saudi Arabia
Fahd N. Al-Wesabi
Department of Computer Science, College of Science & Art at Mahayil, King Khalid University, Saudi Arabia; Corresponding author.
Muhammad Assam
College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
Barnacles Mating Optimizer (BMO) is a new metaheuristic algorithm that suffers from slow convergence and poor efficiency due to its limited capability in exploiting the search space and exploring new promising regions. Addressing these shortcomings, this paper introduces Elitist Barnacles Mating Optimizer (eBMO). Unlike BMO, eBMO exploits the elite exponential probability (Pelite) to decide whether to intensify search process via swap operator or to diversify search by randomly exploring new regions. Furthermore, eBMO uses Chebyshev map instead of random numbers to generate quality S-boxes. Experimental results of eBMO on the generation of 8 × 8 substitution-box are competitive against other existing works.
