具有内在相关性的激光相位噪声量子随机数发生器的安全性评估
Security Evaluation of Laser-Phase-Noise Quantum Random Number Generators with Intrinsic Correlations
AI总结：
研究激光相位噪声量子随机数发生器安全性，通过建立相关性分析模型及表达式量化可提取随机性，经模拟和实验验证模型有效，发现忽略内在相关性会高估可提取随机性约46%，为高性能量子随机数发生器设计提供理论框架。
AI中文摘要：
量子随机数发生器对于实现现代密码系统中的信息理论安全至关重要。在各种实现方式中，激光相位噪声方案因其简单的架构和高集成潜力而受到广泛青睐。然而，原始数据中的内在相关性常常被忽视，这违反了独立同分布假设并可能危及系统安全。在这项工作中，我们建立了相关性分析模型，并针对存在内在相关性时的条件最小熵制定了分析表达式，以准确量化真正可提取的随机性。数值模拟和实验结果证实了我们理论模型的有效性，二者表现出极佳的一致性。在典型设置下，结果表明忽略内在相关性会导致可提取随机性被高估约46%。这项工作为设计具有严格安全分析的紧凑、高性能量子随机数发生器提供了有价值的理论框架。
英文摘要：
Quantum random number generators are essential for achieving information-theoretical security in modern cryptographic systems. Among various implementations, laser phase noise schemes are widely favored for their simple architecture and high integration potential. However, the intrinsic correlations in the raw data are often neglected, which violates the independent and identically distributed assumption and potentially compromises system security. In this work, we establish an analytical model of correlation and formulate an analytical expression for the conditional min-entropy in the presence of intrinsic correlations to accurately quantify the genuinely extractable randomness. The validity of our theoretical model is confirmed by numerical simulations and experimental results, exhibiting excellent agreement. Under typical setups it is shown that neglecting intrinsic correlations leads to an overestimation of extractable randomness by approximately 46%. This work provides a valuable theoretical framework for designing compact, high-performance quantum random number generators with rigorous security analysis.
