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arXiv:1205.4977

LDPC for QKD Reconciliation

Alan Mink, Anastase Nakassis

Published May 22, 2012• 14 citations
arXivHTMLPDF

Abstract

We present the Low Density Parity Check (LDPC) forward error correction algorithm adapted for the Quantum Key Distribution (QKD) protocol in a form readily applied by developers. A sparse parity check matrix is required for the LDPC algorithm and we suggest using some that have been defined by the IEEE and ETSI standards organizations for use in various communication protocols. We evaluate the QKD performance of these various parity check matrices as a function of the quantum bit error rate. We also discuss the computational precision required for this LPDC algorithm. As QKD evolves towards deployment, complete algorithm descriptions and performance analysis, as we present, will be required.

DOI
10.48550/arxiv.1205.4977

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We present the Low Density Parity Check (LDPC) forward error correction algorithm adapted for the Quantum Key Distribution (QKD) protocol in a form readily applied by developers. A sparse parity check matrix is required for the LDPC algorithm and we suggest using some that have been defined by the IEEE and ETSI standards organizations for use in various communication protocols. We evaluate the QKD performance of these various parity check matrices as a function of the quantum bit error rate. We also discuss the computational precision required for this LPDC algorithm. As QKD evolves towards deployment, complete algorithm descriptions and performance analysis, as we present, will be required.
In this paper, the parity-check matrices that can be used in low density parity check (LDPC) based error correction method for quantum key distribution are analyzed. The quantum key distribution system has inevitable errors in sifted key that must be corrected by an error correction algorithm to create a secure key. In this analysis, 1000-bit sifted keys are divided into 50 parts. The algorithm creates 50 syndromes corresponding to each part by multiplying 10 × 20 bit parity-check matrices. The algorithm sends the generated syndrome to the other side, which also divides the sifted key into 50 parts, creates a syndrome from each part, and compares with the received syndrome. If the syndromes are different, these sifted key parts are discarded. However, there may be situations where different parts may have the same syndromes. Therefore, it is necessary to find such an optimal matrix that removes the probability of getting the same syndromes at different parts of the sifted key.
We present a new error correction protocol for quantum key distribution using forward error correction techniques which is suitable for very high‐speed implementations. Using low‐density parity‐check codes, this protocol can achieve an order of magnitude greater efficiency than Cascade in communication cost and computation speed, with only slightly greater overhead in the number of parity bits revealed on the public channel. This protocol has been implemented on the DARPA quantum network between BBN, Harvard University and Boston University.
Quantum Key Distribution (QKD) is a revolutionary security technology that exploits the laws of quantum mechanics to achieve information-theoretic secure key exchange. QKD enables two parties to “grow” a shared secret key without placing any limits on an adversary’s computational power. Error reconciliation protocols have been developed that preserve security while allowing a sender and receiver to reconcile the errors in their respective keys. The most famous of these is the Cascade protocol, which is effective but suffers from a high communication complexity and low throughput. The Winnow protocol reduces the communication complexity over Cascade, but has the disadvantage of introducing errors. Finally, Low Density Parity Check (LDPC) codes have been shown to reconcile errors at rates higher than those of Cascade and Winnow, but with greater computational complexity. In this paper we evaluate the effectiveness of LDPC codes by comparing the runtime, throughput and communication complexity empirically with the Cascade and Winnow algorithms. The effects of inaccurate error estimation, non-uniform error distribution and varying key length on all three protocols are evaluated for identical input key strings. Analyses are performed on the results in order to characterize the strengths and weaknesses of each protocol.
Abstract : Quantum Key Distribution (QKD) is a method for transmitting a cryptographic key between a sender and receiver in a theoretically unconditionally secure way. Unfortunately, the present state of technology prohibits the flawless quantum transmission required to make QKD a reality. For this reason, error reconciliation protocols have been developed which preserve security while allowing a sender and receiver to reconcile the errors in their respective keys. The most famous of these protocols is Brassard and Salvail's Cascade, which is effective, but suffers from a high communication complexity and therefore results in low throughput. Another popular option is Buttler's Winnow protocol, which reduces the communication complexity over Cascade, but has the added detriment of introducing errors, and has been shown to be less effective than Cascade. Finally, Gallager's Low Density Parity Check (LDPC) codes have recently been shown to reconcile errors at rates higher than those of Cascade and Winnow with a large reduction in communication, but with greater computational complexity. This research seeks to evaluate the effectiveness of these LDPC codes in a QKD setting, while comparing real-world parameters such as runtime, throughput and communication complexity empirically with the well-known Cascade and Winnow algorithms. Additionally, the effects of inaccurate error estimation, non-uniform error distribution and varying key length on all three protocols are evaluated for identical input key strings. Analyses are performed on the results in order to characterize the performance of all three protocols and determine the strengths and weaknesses of each.
Low Density Parity Check (LDPC) error correction is a one-way algorithm that has become popular for quantum key distribution (QKD) post-processing. Graphic processing units (GPUs) provide an interesting attached platform that may deliver high rates of error correction performance for QKD. We present the details of our various LDPC GPU implementations and both error correction and execution throughput performance that each achieves. We also discuss the potential for implementation on a GPU platform to achieve Gbit/s throughput.