Randomness Evaluation of a Genetic Algorithm for Image Encryption: A Signal Processing Approach

TL;DR

This paper evaluates the randomness of a novel image encryption method using a genetic algorithm inspired by bacterial resistance, demonstrating its effectiveness through statistical tests and comparing its performance favorably to chaos-based ciphers.

Contribution

Introduces the GFHT genetic algorithm for image encryption, combining gene fusion and horizontal gene transfer, with a novel randomness evaluation approach validated by extensive experiments.

Findings

Encrypted images exhibit statistical properties of white noise

Achieves 99% avalanche effect with one-time pad modifications

Outperforms chaos-genetic ciphers in efficiency and security

Abstract

In this paper a randomness evaluation of a block cipher for secure image communication is presented. The GFHT cipher is a genetic algorithm, that combines gene fusion (GF) and horizontal gene transfer (HGT) both inspired from antibiotic resistance in bacteria. The symmetric encryption key is generated by four pairs of chromosomes with multi-layer random sequences. The encryption starts by a GF of the principal key-agent in a single block, then HGT performs obfuscation where the genes are pixels and the chromosomes are the rows and columns. A Salt extracted from the image hash-value is used to implement one-time pad (OTP) scheme, hence a modification of one pixel generates a different encryption key without changing the main passphrase or key. Therefore, an extreme avalanche effect of 99% is achieved. Randomness evaluation based on random matrix theory, power spectral density, avalanche effect, 2D auto-correlation, pixels randomness tests and chi-square hypotheses testing show that encrypted images adopt the statistical behavior of uniform white noise; hence validating the theoretical model by experimental results. Moreover, performance comparison with chaos-genetic ciphers shows the merit of the GFHT algorithm.