A Lightweight Hybrid Random Number Generator With Dynamic Entropy Injection

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.

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Publication Details

Journal
IEEE Open Journal of Circuits and Systems
Published
2025-01-01
DOI
https://doi.org/10.1109/ojcas.2025.3582975
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
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article

A Lightweight Hybrid Random Number Generator With Dynamic Entropy Injection

Magdy Bayoumi, Kasem Khalil, Shelby Williams, Sonia Akter et al.
IEEE Open Journal of Circuits and Systems
Chaos-based Image/Signal Encryption
article

A Lightweight Hybrid Random Number Generator With Dynamic Entropy Injection

Magdy Bayoumi, Kasem Khalil, Shelby Williams, Sonia Akter, Prosen Kirtonia
article en

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.

IEEE Open Journal of Circuits and SystemsVol. 6
University of Mississippi (US), University of Louisiana at Lafayette (US)
Affordable and clean energy
Openalex Percentile: Top 83%
Chaos-based Image/Signal Encryption
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A Lightweight Hybrid Random Number Generator With Dynamic Entropy Injection — Magdy Bayoumi, Kasem Khalil, et al. · IEEE Open Journal of Circuits and Systems (2025) | TGRS Research Map | TGRS