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Secure synchronization of artificial neural networks used to correct errors in quantum cryptography. (arXiv:2301.11440v1 [cs.CR])
cs.CR updates on arXiv.org arxiv.org
Quantum cryptography can provide a very high level of data security. However,
a big challenge of this technique is errors in quantum channels. Therefore,
error correction methods must be applied in real implementations. An example is
error correction based on artificial neural networks. This paper considers the
practical aspects of this recently proposed method and analyzes elements which
influence security and efficiency. The synchronization process based on mutual
learning processes is analyzed in detail. The results allowed us to determine …
artificial big challenge cryptography data data security efficiency error errors high influence networks neural networks process quantum quantum cryptography security synchronization