A New Randomness Evaluation Method with Applications to Image Shuffling and Encryption

TL;DR

This paper introduces a novel statistical method based on a Z-test to evaluate the randomness of images, particularly useful for assessing shuffled or encrypted images, with robust simulation results demonstrating its effectiveness.

Contribution

It presents a new mathematical model for perfectly shuffled images, derives their pixel difference distribution, and proposes an unbiased randomized algorithm for evaluating image randomness.

Findings

The method accurately distinguishes shuffled/encrypted images from random ones.

It outperforms traditional binary data testing schemes like NIST 800-22.

The approach is robust and effective in practical image applications.

Abstract

This letter discusses the problem of testing the degree of randomness within an image, particularly for a shuffled or encrypted image. Its key contributions are: 1) a mathematical model of perfectly shuffled images; 2) the derivation of the theoretical distribution of pixel differences; 3) a new $Z$-test based approach to differentiate whether or not a test image is perfectly shuffled; and 4) a randomized algorithm to unbiasedly evaluate the degree of randomness within a given image. Simulation results show that the proposed method is robust and effective in evaluating the degree of randomness within an image, and may often be more suitable for image applications than commonly used testing schemes designed for binary data like NIST 800-22. The developed method may be also useful as a first step in determining whether or not a shuffling or encryption scheme is suitable for a particular cryptographic application.