Shannon Entropy based Randomness Measurement and Test for Image Encryption

TL;DR

This paper introduces a new entropy-based randomness measurement for image encryption that evaluates local block randomness, providing a more accurate assessment of encryption quality than traditional Shannon entropy.

Contribution

It proposes a novel block-based entropy measurement and hypothesis testing method for evaluating the randomness of encrypted images, addressing limitations of existing global entropy measures.

Findings

The new test effectively distinguishes well-encrypted images from poorly encrypted ones.

It provides both quantitative and qualitative assessment tools for image encryption quality.

The method can be extended to other digital data like audio and video.

Abstract

The quality of image encryption is commonly measured by the Shannon entropy over the ciphertext image. However, this measurement does not consider to the randomness of local image blocks and is inappropriate for scrambling based image encryption methods. In this paper, a new information entropy-based randomness measurement for image encryption is introduced which, for the first time, answers the question of whether a given ciphertext image is sufficiently random-like. It measures the randomness over the ciphertext in a fairer way by calculating the averaged entropy of a series of small image blocks within the entire test image. In order to fulfill both quantitative and qualitative measurement, the expectation and the variance of this averaged block entropy for a true-random image are strictly derived and corresponding numerical reference tables are also provided. Moreover, a hypothesis test at significance-level is given to help accept or reject the hypothesis that the test image is ideally encrypted/random-like. Simulation results show that the proposed test is able to give both effectively quantitative and qualitative results for image encryption. The same idea can also be applied to measure other digital data, like audio and video.