An Efficient Meta-Heuristic Chemical Reaction Optimization Based Algorithm for Association Rule Hiding Using an Advanced Perturbation Approach

摘要

Meta-heuristic approaches like genetic algorithm, particle swarm, chemical reaction and cuckoo optimization algorithms have a trade-off in the reduction of ghost rules and lost rules in association rule hiding. The implications found in this context are motivating the researchers towards novel metaheuristic chemical reaction optimization algorithm based on data modification algorithm. This paper inherits the chemical reaction optimization functionalities and has been used for association rule hiding. It produces better results in comparison with Genetic Algorithm based, Particle Swarm Optimization based, Cuckoo based alaorithms.