CRYPTO-MINE: Cryptanalysis via Mutual Information Neural Estimation. (arXiv:2309.08019v1 [cs.CR])

The use of Mutual Information (MI) as a measure to evaluate the efficiency of
cryptosystems has an extensive history. However, estimating MI between unknown
random variables in a high-dimensional space is challenging. Recent advances in
machine learning have enabled progress in estimating MI using neural networks.
This work presents a novel application of MI estimation in the field of
cryptography. We propose applying this methodology directly to estimate the MI
between plaintext and ciphertext in a chosen plaintext attack. The …

cryptanalysis crypto efficiency high history information machine machine learning measure networks neural networks novel progress random space work