In this paper, we have proposed asymmetric image encryption cum authentication cryptosystem based on double random modulus decomposition using computational ghost imaging in the Fourier domain. The literature demonstrates that image encryption algorithms relying on double random modulus decomposition are susceptible to iterative cryptographic attacks. Computational ghost imaging is used to enhance the security of double random modulus decomposition-based cryptosystem and resistant to iterative cryptographic attack. The encrypted image is quite random and appear noisy and can be used for encryption as well as authentication purpose. The proposed cryptosystem is validated for binary, grayscale and medical images. Various statistical metrics, such as mean squared error, information entropy, and correlation coefficient, are applied to analyse the strength of the cryptosystem. Statistical attacks in terms of correlation distribution plots, 3-D plots are performed on the cryptosystem. The results indicate that the cryptosystem is robust against statistical attacks. All decryption keys are essential for faithful recovery of the original image as well as in the authentication cryptosystem. However, in the authentication cryptosystem, we have shown that if more than 6% of any individual key data are lost, cryptosystem fail to recognise the image. Therefore, the proposed encryption cum authentication cryptosystem is safe and secure.
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