2021/04/22 by Miłosz Stypiński, Stypiński, Miłosz, Marcin Niemiec +1
Agricultural and Biological Sciences · Computer Science · Engineering · #Advanced Research in Systems and Signal Processing #Advanced Scientific Research Methods #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Mathematical Control Systems and Analysis #Neural and Evolutionary Computing (cs.NE)
paper · doi:10.48550/arxiv.2104.11105
openalex publication_date 2021/04/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Neural cryptography is the application of artificial neural networks in the subject of cryptography. The functionality of this solution is based on a tree parity machine. It uses artificial neural networks to perform secure key exchange between network entities. This article proposes improvements to the synchronization of two tree parity machines. The improvement is based on learning artificial neural network using input vectors which have a wider range of values than binary ones. As a result, the duration of the synchronization process is reduced. Therefore, tree parity machines achieve common weights in a shorter time due to the reduction of necessary bit exchanges. This approach improves the security of neural cryptography