2D Logistic-Sine-coupling map for image encryption

Abstract Image encryption is a straightforward strategy to protect digital images by transforming images into unrecognized ones. The chaos theory is a widely used technology for image encryption as it has many significant properties such as ergodicity and initial state sensitivity. When chaotic systems are used in image encryption, their chaos performance highly determines the security level. This paper presents a two-dimensional (2D) Logistic-Sine-coupling map (LSCM). Performance estimations demonstrate that it has better ergodicity, more complex behavior and larger chaotic range than several newly developed 2D chaotic maps. Utilizing the proposed 2D-LSCM, we further propose a 2D-LSCM-based image encryption algorithm (LSCM-IEA), which adopts the classical confusion-diffusion structure. A permutation algorithm is designed to permutate image pixels to different rows and columns while a diffusion algorithm is developed to spread few changes of plain-image to the whole encrypted result. We compare the efficiency of LSCM-IEA with several advanced algorithms and the results show that it has higher encryption efficiency. To show the superiority of LSCM-IEA, we also analyze the security of LSCM-IEA in terms of key security, ability of defending differential attack, local Shannon entropy and contrast analysis. The analysis results demonstrate that LSCM-IEA has better security performance than several existing algorithms.