Comparison of ACM and GRP Methods for Image Permutation

In this code example, Performance evaluations for Group (GRP) and Arnold’s Cat Map (ACM) method are analyzed.

Permutation and substitution processes of an image are most widely used in image encryption algorithms as they are thought to increase system security in cryptography. Permutation is the first process that all pixel positions in an image are shuffled in specific order or randomly in order to break strong correlation between pixels. Secondly, substitution is used to change pixel values by mixing a secret key in the permutated image. In an ordinary image, adjacent pixels have close values so they have strong correlation and this correlation needs to be broken effectively before encryption. The degree to which this process is performed, directly affects the overall system security. In this paper, performance evaluations for Group (GRP) and Arnold’s Cat Map (ACM) method are analyzed through some numerical results and their performances are compared to figure out which one is better. Experimental results consist of numerical and visual results determined in Matlab R2015a.