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arXiv:1810.05841 · Journal of Russian Laser Research

Error Estimation at the Information Reconciliation Stage of Quantum Key Distribution

Evgeniy O. Kiktenko, Aleksei Malyshev, A. A. Bozhedarov, N. O. Pozhar, M. N. Anufriev, Aleksey K. Fedorov

Published Nov 1, 2018• 22 citations
arXivHTMLPDF
DOI
10.1007/s10946-018-9752-y

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arXiv:1902.05263•Optics Express•May 6, 2019•23 citations
Quantum Key Distribution (QKD) is a promising field in modern cryptography where the security of key information is guaranteed by the laws of quantum mechanics. One of the key stages in QKD protocols is error estimation and reconciliation in the secret key. This procedure requires the transmission of a certain number of secret key bits over a public channel. Such transmission leads to disclosing these bits to a potential eavesdropper. The fraction of disclosed bits—the sampling rate-largely depends on the chosen approach for preliminary error estimation in the channel. This work is devoted to the optimization of the sampling rate for an LDPC code from the 5G\mathbf{5 G}5G standard. The results of our experiments show that for a QBER below 0.2 and key lengths of 264, 528, 792, and 1056 bits, it is necessary to disclose no more than 18%,11%,10%18 \%, 11 \%, 10 \%18%,11%,10%, and 7%7 \%7% of the key bits for error estimation, respectively. Furthermore, the proposed algorithm allows for similar optimization for any information reconciliation protocols and actual quantum bit error rates.
Post-processing is a significant step in quantum key distribution (QKD), which is used for correcting the quantum-channel noise errors and distilling identical corrected keys between two distant legitimate parties. Efficient error reconciliation protocol, which can lead to an increase in the secure key generation rate, is one of the main performance indicators of QKD setups. In this paper, we propose a multi-low-density parity-check codes based reconciliation scheme, which can provide remarkable perspectives for highly efficient information reconciliation. By testing our approach through data simulation, we show that the proposed scheme combining multi-syndrome-based error rate estimation allows for a more accurate estimation of the error rate as compared with random sampling and single-syndrome estimation techniques before the error correction, as well as a significant increase in the efficiency of the procedure without compromising security and sacrificing reconciliation efficiency.