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

中文翻译：

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使用非二进制输入向量同步树型奇偶校验机

神经密码术是人工神经网络在密码学领域的应用。该解决方案的功能基于树型奇偶校验机。它使用人工神经网络在网络实体之间执行安全的密钥交换。本文提出了对两个树奇偶校验机同步的改进。改进基于使用输入向量学习人工神经网络，该输入向量的值范围比二进制值大。结果，减少了同步过程的持续时间。因此，由于减少了必要的位交换，树型奇偶校验机在较短的时间内实现了通用权重。这种方法提高了神经密码学的安全性