Improved ECC-Based Image Encryption with 3D Arnold Cat Map

Maintaining the secrecy and safety of images while sharing digital data online is a huge challenge. Numerous encryption schemes use the Elliptic Curve Cryptography(ECC) to encrypt and decrypt the images as ECC provides higher security with shorter key sizes. The researchers also suggest the use of the popular chaotic maps for added strength of the encryption process. In this paper, a novel encryption scheme for digital images based on ECC and 3D Arnold cat map is proposed. The 3D Arnold cat map scrambles the position of pixels in the image and then transforms the values of pixels. The transformed pixel values are encrypted and decrypted using the Elliptic Curve Analogue ElGamal Encryption Scheme (ECAEES). The proposed model is implemented using Python. We get an average entropy value of 7.9992, NPCR of 99.6%, UACI of 33.3% and PSNR of 27.89. The correlation coefficient values between adjacent pixels of cipher images are minimized. The improved performance proves that the model put forward is more secure and resilient than the existing noteworthy schemes.