Contribution to Symmetric Cryptography by Convolutional Neural Networks
Radoslav Forgáč, Miloš Očkay · 2019
This paper presents an implementation of Convolutional Neural Network (CNN) symmetric encryption. The results based on selected criteria are compared with Advanced Encryption Standard (AES). Authors are testing both implementations using the set of differently sized and content independent files. Compared metrics include the execution time, memory occupancy and processor load. Robustness of CNN encryption against the crypto attacks was not tested and it is out of the scope of this paper. Concluded results offer the usability prospects of selected neural network for symmetric cryptographic purposes. The results of the experiments have shown that CNN has the potential for cryptographic purposes under the conditions specified in this paper.