When Mini-AES Meets Machine Learning: Practice and Experience
Xian Liu · 2020
It is interesting to investigate the decryptability of machine learning methodology for a compact block cypher: Mini-AES. In the present work, we design a neural network with three hidden layers and a moderate number of neurons. Trained by a moderate number of random pairs of plaintext and ciphertext, this neural network can successfully decrypt Mini-AES.