A Lightweight Hybrid Random Number Generator With Dynamic Entropy Injection

IF 2.4 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Sonia Akter;Shelby Williams;Prosen Kirtonia;Magdy Bayoumi;Kasem Khalil
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Abstract

This paper presents a lightweight hybrid random number generator (HRNG), implemented and evaluated on a Field-Programmable Gate Array (FPGA). The proposed design enhances security and randomness by synergizing jitter and metastability using a feedforward topology, which achieves a near-perfect Shannon entropy. Moreover, it is validated using three distinct entropy metrics, guaranteeing statistically robust random numbers for security-sensitive applications. In addition to entropy evaluations, this design is also rigorously analyzed using multiple industry-standard randomness test suites. Beyond the FPGA implementation, this work presents performance metrics, including area utilization, power consumption, maximum frequency, and energy usage per random bit, which are synthesized across three different technology nodes in Synopsys Design Compiler (SDC). All of the results from the FPGA and the SDC implementations demonstrate significant improvements. These results confirm the design’s scalability to advance technology nodes and its suitability for applications that require secure and reliable random number generation, such as resource-efficient Internet of Things (IoT) devices.
具有动态熵注入的轻量级混合随机数生成器
本文提出了一种轻量级混合随机数发生器(HRNG),并在现场可编程门阵列(FPGA)上实现和评估。提出的设计通过使用前馈拓扑协同抖动和亚稳态来增强安全性和随机性,从而实现近乎完美的香农熵。此外,它使用三个不同的熵度量进行验证,保证对安全敏感的应用程序具有统计上健壮的随机数。除了熵评估之外,该设计还使用多个行业标准随机测试套件进行了严格分析。除了FPGA实现之外,这项工作还提供了性能指标,包括面积利用率、功耗、最大频率和每个随机比特的能量使用,这些指标是在Synopsys设计编译器(SDC)中的三个不同技术节点上合成的。FPGA和SDC实现的所有结果都显示出显着的改进。这些结果证实了该设计的可扩展性,以推进技术节点,并适用于需要安全可靠的随机数生成的应用,如资源节约型物联网(IoT)设备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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