A Secure Image Encryption Algorithm Based on Rubik′s Cube Principle

Abstract

In the past few years, several encryption algorithms based on chaotic systems have been proposed as means to protect digital images against cryptographic attacks. These encryption algorithms typically use relatively small key spaces and thus offer limited security, especially if they are one-dimensional. In this paper, we proposed a novel image encryption algorithm based on Rubik's cube principle. The original image is scrambled using the principle of Rubik's cube. Then, XOR operator is applied to rows and columns of the scrambled image using two secret keys. Finally, the experimental results and security analysis show that the proposed image encryption scheme not only can achieve good encryption and perfect hiding ability but also can resist exhaustive attack, statistical attack, and differential attack.

A Secure Algorithm for Region of Interest (ROI) Encryption for RGB Color Images

“…Other notable approaches include that due to Loukhoukha, Chouinard and Berdai [11] which is based on the principle of Rubiks Cube. The method was shown to have appreciable resistance to brute force attack.…”

Effect of Encryption Technique and Size of Image on Correlation Coefficient in Encrypted Image

“…Four different techniques affine transformation and XOR operation [3] one-dimensional random scrambling [4] XOR operation and rotation [5] Three distinct onedimensional chaotic map [7] …”

“…So, different criteria are used to measure the capability of an image encryption algorithm and security level of encrypted image. One significant criterion is the correlation coefficient that is used for statistical analysis of encrypted image [4].…”

“…Correlation coefficient assesses the correlation between two adjoining pixels in an image [4,5]. Generally, correlation measures the degree of similarity between two pixels.…”

“…An encrypted image should have low correlation between two adjoining pixels [4,5,6], so that it becomes difficult to guess the value of neighbors of a pixel. For example, xi and yi are two pixel pair then the correlation coefficient can be obtained by the equation (4) [4,5,6]. The rest of the paper is divided as: existing algorithms that will be used for experiment, experimental results, conclusion and suggested future work.…”