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Error correction in quantum cryptography based on artificial neural networks

机译:基于人工神经网络的量子密码术纠错

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摘要

Intensive work on quantum computing has increased interest in quantum cryptography in recent years. Although this technique is characterized by a very high level of security, there are still challenges that limit the widespread use of quantum key distribution. One of the most important problems remains secure and effective mechanisms for the key distillation process. This article presents a new idea for a key reconciliation method in quantum cryptography. This proposal assumes the use of mutual synchronization of artificial neural networks to correct errors occurring during transmission in the quantum channel. Users can build neural networks based on their own string of bits. The typical value of the quantum bit error rate does not exceed a few percent; therefore, the strings are similar and also users' neural networks are very similar at the beginning of the learning process. It has been shown that the synchronization process in the new solution is much faster than in the analogous scenario used in neural cryptography. This feature significantly increases the level of security because a potential eavesdropper cannot effectively synchronize their own artificial neural networks in order to obtain information about the key. Therefore, the key reconciliation based on the new idea can be a secure and efficient solution.
机译:近年来,对量子计算的密集工作增加了对量子密码的兴趣。虽然这种技术的特点是安全性很高,但仍有仍然限制量子密钥分布的广泛使用的挑战。最重要的问题之一仍然是关键蒸馏过程的安全有效机制。本文为量子密码术提供了一个关键调和方法的新想法。该提议假设使用人工神经网络的相互同步来校正在量子信道中在传输期间发生的错误。用户可以根据自己的串词构建神经网络。量子钻头错误率的典型值不超过少量百分比;因此,字符串类似,并且用户的神经网络在学习过程的开始时非常相似。已经表明,新解决方案中的同步过程比神经密码术中使用的类似场景更快。这种特征显着提高了安全水平,因为潜在的窃听者无法有效地同步他们自己的人工神经网络,以便获得有关密钥的信息。因此,基于新想法的关键和解可以是安全有效的解决方案。

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