Breaking a chaotic image encryption algorithm - Noshadian, Saeed; Ebrahimzade, Ata; Kazemitabar, Seyed Javad (Multimedia tools and applications, 2020)
Image encryption is an important issue in information security. Due to sensitivity to initial values, randomness and simple computation, chaos-based image encryption algorithms efficiently provide security. In a recent paper a chaos-based image encryption was proposed that employs genetic algorithm to optimize correlation between adjacent pixels. We show via simulations a security exploit that can find the key and decrypt the image. To fix the the aforementioned vulnerability we harness Knuth shuffle where we replace the rand function with the logistic map. We then evaluate the security of our proposed algorithm by testing the impact of several attacks on it. We show that while improving the security, our algorithm keeps the same level of pixel entropy as the previous method. Moreover, the correlation coefficient among adjacent pixels of the cipher image was reduced by an order of magnitude.