《计算机应用研究》|Application Research of Computers

基于误码率模型的Cascade协议动态初始分块策略研究

Dynamic initial block-size strategy research of Cascade protocol based on error rate model

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作者 赵红涛,孙万忠,栾欣
机构 解放军信息工程大学 河南省信息安全重点实验室,郑州 450001
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文章编号 1001-3695(2015)01-0236-03
DOI 10.3969/j.issn.1001-3695.2015.01.054
摘要 为了提高Cascade协议的纠错效率,提出了一种新的基于贝叶斯决策理论和泊松随机过程的动态调整初始化分块大小的策略。该方法引入误码率模型的概念,根据误码率随时间变化快慢的特点及其分布规律,构建了三种不同的误码率模型。 实验结果表明,根据误码率模型动态调整Cascade协议初始分块大小,有效减少了信息泄露,显著提高了纠错的效率,对于QKD效率的提高有重要意义。
关键词 量子密钥分配;Cascade协议;误码率模型;初始化分块;贝叶斯决策理论
基金项目 国家重大科技专项资助项目(2012ZX0102700K)
本文URL http://www.arocmag.com/article/01-2015-01-054.html
英文标题 Dynamic initial block-size strategy research of Cascade protocol based on error rate model
作者英文名 ZHAO Hong-tao, SUN Wan-zhong, LUAN Xin
机构英文名 Henan Key Laboratory of Information Security, PLA Information Engineering University, Zhengzhou 450001, China
英文摘要 To boost the efficiency of the Cascade protocol, this paper proposed a new strategy based on Bayesian decision theory and Poisson stochastic process which adjusted the initial block-size dynamic. The new method was based on the novel notion of the error rate model. It studied error rate model features, which were its distribution rules and its varying speed, and introduced three error rate models. The experiments show that due to dynamic adjusting the initial block-size of the Cascade protocol based on error rate models, the number of bits revealed to the adversary is reduced and it significantly increases the efficiency of the error correction. This leads to a considerable improvement of the QKD’s efficiency.
英文关键词 quantum key distribution(QKD); Cascade protocol; error rate model; initial block-size; Bayesian decision theory
参考文献 查看稿件参考文献
  [1] GILBERT G, HAMRICK M. Practical quantum cryptography:a comprehensive analysis (part one)[EB/OL] . (2000). http://www. citebase. org/abstract?id=oai:arXiv. org:quant-ph/00%9027.
[2] BENNETT C H, BESSETTE F, BRASSARD G, et al. Experimental quantum cryptography[J] . Journal of Cryptology, 1992, 5(1):3-28.
[3] ROBERT C P. The Bayesian choice[M] . New York:Springer, 2001.
[4] GRANDELL J. Doubly stochastic Poisson processes[M] . New York:Springer, 1976.
[5] KINGMAN J. Poisson processes[M] . Oxford:Oxford Science Publications, 1993.
[6] SHERMAN J, MORRISON W J. Adjustment of an inverse matrix corresponding to a change in on element of a given matrix[J] . The Annals of Mathematical Statistics, 1950, 21(1):124-127.
[7] TEUKOLSKY W H. Numerical recipes in C[M] . 2nd ed. New York:Cambridge University Press, 1992.
[8] ROSS S M. Stochastic processes:series in probability and mathematical statistics[M] . New York:Wiley, 1983.
[9] BROCKWELL P J, DAVIS R A. Introduction to time series and forecasting[M] . New York:Springer, 1996.
[10] STULAJTER F. Predictions in time series using regression models[M] . New York:Springer, 2002.
收稿日期 2013/12/5
修回日期 2014/3/1
页码 236-238
中图分类号 TP309.2
文献标志码 A