Two improved metaheuristic techniques and their applications in automated cryptanalysis of knapsack cryptosystems
Ashish Kumar Jain, Manoj Kumar Bohra · International Journal of Bio-Inspired Computation · 2022
During the past decade, considerable improved versions of real particle swarm optimisation (PSO) have been proposed in the literature. However, only a few significant improved versions of binary PSO (BPSO) have been reported. For efficiently solving binary optimisation problems, this paper proposes an improved-BPSO technique in which an improved idea for updating particles' velocity is proposed. To escape from the local optimum, an on/off mutation strategy is also introduced. Thereafter, the proposed strategy is utilised to solve two reduced knapsack cryptosystems. For a fair assessment of the proposed technique two relatively new methods are also utilised, namely, novel-BPSO and modified-BPSO. This paper also proposes an improved genetic algorithm (improved-GA) for solving the considered knapsack cryptosystems. Finally, the experimental results are analysed by performing f-test and t-test. The outcomes obtained indicate that the improved-GA and improved-BPSO strategies solve the considered automated cryptanalysis problem efficiently in terms of accuracy and convergence.