Image Cryptography with Chaos: Testing the k-epsilon Turbulence Model as a Chaos Generator

Abstract

Cryptography has uses in everyday applications ranging from e-commerce transactions to military communications. Traditional approaches for encrypting images has been performed by processing an input image as a one-dimensional stream of bits before applying the encryption algorithms. There is current research in manipulating images in their native two-dimensional form rather than as a one-dimensional stream. To do this, deterministic chaos maps have been explored for their use in providing the operations required to transform a plaintext image into a ciphertext encrypted image and vice versa. Different approaches for generating chaos maps have been explored ranging from cellular automata to bio-inspired algorithms. This research aims to borrow a deterministic chaos technique from the field of Computational Fluid Dynamics that is used to simulate turbulence in fluid systems. The feasibility of using this technique as a chaos generator will be quantitatively determined using cryptanalysis techniques including measuring the luminance histograms, various image spectra, and pixel covariant dependence.