True Random Number Generators (TRNGs) are indispensable in modern cryptosystems. Unfortunately, to guarantee high entropy of the generated numbers, many TRNG designs require a complex implementation procedure, often involving manual placement and routing. In this work, we introduce, analyse, and compare three dynamic calibration mechanisms for the COherent Sampling ring Oscillator based TRNG: GateVar , WireVar , and LUTVar , enabling easy integration of the entropy source into complex systems. The TRNG setup procedure automatically selects a configuration that guarantees the security requirements. In the experiments, we show that two out of the three proposed mechanisms are capable of assuring correct TRNG operation even when an automatic placement is carried out and when the design is ported to another Field-Programmable Gate Array (FPGA) family. We generated random bits on both a Xilinx Spartan 7 and a Microsemi SmartFusion2 implementation that, without post processing, passed the AIS-31 statistical tests at a throughput of 4.65 Mbit/s and 1.47 Mbit/s, respectively.

中文翻译：

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基于相干采样的真随机数生成可配置环形振荡器的设计与分析

真随机数生成器 (TRNG) 在现代密码系统中是必不可少的。不幸的是，为了保证生成数字的高熵，许多 TRNG 设计需要复杂的实现过程，通常涉及手动布局和布线。在这项工作中，我们介绍、分析和比较了基于相干采样环振荡器的 TRNG 的三种动态校准机制：门控变量,WireVar， 和LUTVar，可以轻松地将熵源集成到复杂系统中。TRNG 设置过程会自动选择保证安全要求的配置。在实验中，我们表明，即使在执行自动放置和将设计移植到另一个时，所提出的三种机制中的两种也能够确保正确的 TRNG 操作现场可编程门阵列 (FPGA)家庭。我们在两个 a 上生成了随机位Xilinx Spartan 7和一个Microsemi SmartFusion2没有后处理的实现，分别以 4.65 Mbit/s 和 1.47 Mbit/s 的吞吐量通过了 AIS-31 统计测试。