Privacy amplification (PA) is an essential part in a quantum key distribution (QKD) system, distilling a highly secure key from a partially secure string by public negotiation between two parties. The optimization objectives of privacy amplification for QKD are large block size, high throughput and low cost. For the global optimization of these objectives, a novel privacy amplification algorithm is proposed in this paper by combining multilinear-modular-hashing and modular arithmetic hashing. This paper proves the security of this hybrid hashing PA algorithm within the framework of both information theory and composition security theory. A scheme based on this algorithm is implemented and evaluated on a CPU platform. The results on a typical CV-QKD system indicate that the throughput of this scheme (261Mbps@2.6*10^8 input block size) is twice higher than the best existing scheme (140Mbps@1*10^8 input block size). Moreover, This scheme is implemented on a mobile CPU platform instead of a desktop CPU or a server CPU, which means that this algorithm has a better performance with a much lower cost and power consumption.
翻译:私隐放大( PA) 是量子键分配( QKD) 系统的一个基本部分, 通过两方之间的公开谈判从部分安全的字符串中提取一个高度安全的密钥 。 QKD 私隐放大的优化目标是大块大小、 高输送量和低成本。 为了在全球优化这些目标,本文件提出了一个新的隐私放大算法, 将多线- 模块- 损耗和模块化算术散列组合在一起 。 本文在信息理论和构成安全理论的框架内证明了这种混合的散列 PA 算法的安全性 。 基于此算法的一个方案在CPU 平台上实施和评估。 典型的 CV- QD 系统的结果显示, 这个方案( 261Mbps@ 2. 6*10 ⁇ 8 输入区块大小) 比现有的最佳方案( 140Mbps@ 1*10 ⁇ 8 输入区块大小高一倍 ) 。 此外, 这个方案是在移动的 CPU 平台上实施的, 而不是一个台式 CPU 或服务器 CPU 。 这意味着这个算算法的性效果更好,, 其成本和消耗力要低得多。