Secure synchronization of artificial neural networks used to correct errors in quantum cryptography

被引：1

作者：

Niemiec, Marcin ^{[1
]}

Widlarz, Tymoteusz ^{[1
]}

Mehic, Miralem ^{[2
,3
]}

机构：

[1] AGH Univ Sci & Technol, Al Mickiewicza 30, PL-30059 Krakow, Poland

[2] Univ Sarajevo, Dept Telecommun, Fac Elect Engn, Sarajevo 71000, Bosnia & Herceg

[3] VSB Tech Univ Ostrava, 17 Listopadu 2172-15, Ostrava 70800, Czech Republic

来源：

ICC 2023-IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS | 2023年

关键词：

quantum cryptography; key reconciliation; error correction; artificial neural networks;

D O I：

10.1109/ICC45041.2023.10279837

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

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 the impact of various parameters. Additionally, the paper describes the recommended number of iterations for different structures of artificial neural networks and various error rates. All this aims to support users in choosing a suitable configuration of neural networks used to correct errors in a secure and efficient way.

引用

页码：3491 / 3496

页数：6

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