Enhanced Visual Cryptography Based on Arnold's Cat Map

Hajir Alauldeen Al-Bayati; Dalal N Hamod; Lahieb M Jawad

Hajir Alauldeen Al-Bayati
Dalal N Hamod
Lahieb M Jawad

Keywords: Visual Cryptography, Chaotic map, Encryption/Decryption, Shares, Security, Blockchain, Real Estate, Agriculture, Healthcare, E-Voting, Data security, Data Transparency.

Abstract

The field of color visual cryptography has experienced significant growth, enabling the secure transmission of color images over the Internet. This innovative methodology partition images into shares, mirroring the principles of Naor and Shamir's approach but tailored specifically for color images. Color visual cryptography (VC) operate by divide color secret images into shares, treat each color pixel individually through the RGB and CMY channels. This study introduces an advanced CVC technique that integrate a chaotic encryption system, significantly enhance security measures. The proposed approach involves extract the channels component and apply a chaotic map to each channel with distinct masks, resulting in the generation of six shares (two for each color channel), subsequently XORing them with a randomly generated key matrix. This process creates new matrices, further enhance security. On the recipient's end, the secret color image is retrieved while maintaining high quality, as evaluated through metrics such as Peak Signal-to-Noise ratio PSNR, Mean Square Error MSE, Correlation Coefficients CC, Number of Pixels Changing Rate NPCR, and Unified Average Change Intensity UACI. Comparative analysis against existing methods demonstrates the superior efficient of this methodology in securely concealing color image secrets. Where the values of each metric were CC =1.0, MSE= 0.0 and PSNR= infinite. While, the best values of NPCR and UACI were 99.65%, 85.62% respectively these for the original channel and associated shares.

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