An Effective Color Image Encryption Based on Henon Map, Tent Chaotic Map, and Orthogonal Matrices

Sensors (Basel). 2022 Jun 8;22(12):4359. doi: 10.3390/s22124359.

Abstract

In the last decade, the communication of images through the internet has increased. Due to the growing demands for data transfer through images, protection of data and safe communication is very important. For this purpose, many encryption techniques have been designed and developed. New and secured encryption schemes based on chaos theory have introduced methods for secure as well as fast communication. A modified image encryption process is proposed in this work with chaotic maps and orthogonal matrix in Hill cipher. Image encryption involves three phases. In the first phase, a chaotic Henon map is used for permuting the digital image. In the second phase, a Hill cipher is used whose encryption key is generated by an orthogonal matrix which further is produced from the equation of the plane. In the third phase, a sequence is generated by a chaotic tent map which is later XORed. Chaotic maps play an important role in the encryption process. To deal with the issues of fast and highly secured image processing, the prominent properties of non-periodical movement and non-convergence of chaotic theory play an important role. The proposed scheme is resistant to different attacks on the cipher image. Different tests have been applied to evaluate the proposed technique. The results of the tests such as key space analysis, key sensitivity analysis, and information entropy, histogram correlation of the adjacent pixels, number of pixel change rate (NPCR), peak signal to noise ratio (PSNR), and unified average changing intensity (UCAI) showed that our proposed scheme is an efficient encryption technique. The proposed approach is also compared with some state-of-the-art image encryption techniques. In the view of statistical analysis, we claim that our proposed encryption algorithm is secured.

Keywords: Henon map; Hill cipher; decryption; image encryption; number of pixel change rate (NPCR); orthogonal matrix; peak signal to noise ratio (PSNR); tent chaotic map; unified average changing intensity (UACI).

Grants and funding

The researchers would like to thank the Deanship of Scientific Research, Qassim University for funding the publication of this project. The authors also thank Natural Sciences and Engineering Research Council of Canada (NSERC) and New Brunswick Innovation Foundation (NBIF) for the financial support of the global project except the publication fees. These granting agencies did not contribute in the design of the study and collection, analysis, and interpretation of data.