Multi-objective optimization of hyperchaotic face image encryption based on particle swarm optimization algorithm
YU Jin-wei
XIE Wei
ZHANG Lang-wen
YU Xiao-yuan
Abstract：In this paper,a particle swarm optimization algorithm(PSO)is combined with a hyperchaotic system to present a face image encryption scheme based on multi-objective optimization.The scheme co-optimises various en-cryption evaluation metrics,including pixel correlation,number of pixel change rate(NPCR),uniform average changing intensity(UACI)and information entropy through the PSO algorithm.Firstly,the control parameters of the chaotic system are initialized,and the initial values of the hyperchaotic system are generated using the SHA-256 algorithm to iteratively produce highly sensitive random sequences.Secondly,the random sequences are used to perform pixel permutation,diffu-sion,and row-column permutation operations,resulting in the initial encrypted face image.Then,the encrypted face image is treated as an individual of the PSO algorithm,and the fitness function considering multiple metrics is optimized by itera-tively updating the individual's position.Finally,the optimal parameters of the hyperchaotic system are determined,and the best encrypted face image is obtained.Experiments demonstrate that the proposed algorithm outperforms the mainstream methods in terms of information entropy,pixel correlation coefficient,NPCR.and UACI,which indicates that the proposed method has higher security.
Keywords：chaotic systemparticle swarm optimization algorithmimage encryptionintelligent optimizationface privacy protection
Publication Date：2025-05-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 875-884 )