| Title | A Primitive Cipher with Machine Learning |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Liu, Xian |
| Conference Name | 2021 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom) |
| Date Published | may |
| Keywords | Artificial neural networks, Ciphers, Conferences, cryptography, Device-to-device communication, edge intelligence, exponentiation, machine learning, mobile edge learning, outsourcing, pubcrawl, resilience, Resiliency, Scalability, Wireless communication |
| Abstract | Multi-access edge computing (MEC) equipped with artificial intelligence is a promising technology in B5G wireless systems. Due to outsourcing and other transactions, some primitive security modules need to be introduced. In this paper, we design a primitive cipher based on double discrete exponentiation and double discrete logarithm. The machine learning methodology is incorporated in the development. Several interesting results are obtained. It reveals that the number of key-rounds is critically important. |
| DOI | 10.1109/BlackSeaCom52164.2021.9527885 |
| Citation Key | liu_primitive_2021 |
A Primitive Cipher with Machine Learning