Chaos-Based Image Encryption Using Arnold’s Cat Map Confusion and Henon Map Diffusion

Abstract

This research designed an image encryption system that focused on securing teledermatology data in the form of skin disease images. The encryption and decryption process of this system is done on the client side using chaos-based encryption with confusion and diffusion techniques. Arnold's cat map is the chaotic map model used for confusion, while the Henon map is used for diffusion. The initial values of both chaotic maps are obtained from a 30-digit secret key that is generated using Diffie-Hellman key exchange. During Arnold's cat map generation, different p and q values are used for every iteration. On the other side, the precision of the Henon map's x and y values is 10-14. From the tests that have been done, histograms of the encrypted images are relatively flat and distributed through all the gray values. Moreover, the encrypted images have average correlation coefficients of 0.003877 (horizontal), -0.00026 (vertical) and -0.00049 (diagonal) and an average entropy of 7.950304. According to the key sensitivity test, a difference of just one number in the secret key causes big differences, as both results have a similarity index of 0.005337 (0.5%). Meanwhile, in the decryption process, that small key difference cannot be used to restore the encrypted image to its original form and generate another chaotic image with average entropies of 7.964909333 (secret key difference) and 7.994861667 (private key difference).

Enhancing Security of Medical Image Data in the Cloud Using Machine Learning Technique

“…Originality: The model developed for image encryption/decryption uses the chaotic mapping with 'Arnoldcat' algorithm. Unlike existing models from the studies [13] (ICA: Independent-Component-Analysis with ACM: ArnoldCat algorithm), [15] (ACM confusion mapping with Henon diffusion mapping), [31] (5 dimensional 3 leaf chaotic model) and [32] (PWLCM: Price-Wise-Linear-Chaotic-Map), the developed research uses Playfairciphering combined with Arnoldcat mapping. Thus the developed model is unique among other medical image encryption/decryption models, especially in cloud storage based security enhancement.…”

Digital Image Encryption using Composition of RaMSH-1 Map Transposition and Logistic Map Keystream Substitution

“…( 9) functions as the PSNR formula, and Eq. ( 10) is used to calculate the MSE value between the original image and the decrypted image [9]. The quality of the decrypted images is evaluated using an RGB image with a resolution of 2850×3200 pixels.…”

“…The encryption process on image with size M≠N is carried out by adding dummy pixels, so the image size is larger than the original size. The limitation in Ratna's research is that the Cat Map transposition function can only carried out in the image with size N×N [9].…”

Physical-Layer Security in Power-Domain NOMA Based on Different Chaotic Maps

“…Initial points x 1 and y 1 [20] act as a symmetric key for a chaotic cryptographic system that is utilized for encryption and decryption at the sender's and receiver's terminals. Since the Hénon map is deterministic, decryption of the cipher image will reconstruct the original image on the receiver's end with the same initial points: x 1 and y 1 [21].…”

“…Arnold's cat map was designed as a confusion technique to randomize the pixel position of an image so that it does not appear the same. This can be achieved using Equation (12) [21]:…”