ITM Web Conf.
Volume 21, 2018Computing in Science and Technology (CST 2018)
|Number of page(s)||6|
|Published online||12 October 2018|
Evolutionary algorithms with and without adaptive mutation in AI based cryptography
Rzeszow University of Technology, Faculty of Electrical and Computer Engineering, Rzeszow, Poland
* Corresponding author: firstname.lastname@example.org
The key role of cryptography is to make cipher so hard to reproduce without knowing all the details that no one besides the recipient could decipher the message. Those algorithms which are used nowadays gets its security mostly from highly reliable algorithms and/or complicated cryptographic keys. Unfortunately, those human-made methods aren‘t invulnerable so sooner or later they compromise. So, it could be really useful to make a cipher which could change. But currently only neural networks are capable of thing known as transfer learning. In this article similar method was proposed in order to make it possible to re-learn already established evolutionary algorithm to do new, similar task.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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