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The growing need for secure and efficient implementations in resource-constrained devices, particularly for Internet of Things (IoT) applications, has accelerated the development of lightweight cryptographic algorithms. This study presents implementation of NIST Lightweight Cryptography (LWC) finalists on both FPGA (Artix-7) and Raspberry Pi platforms and their performances are evaluated as well as compared. On FPGA platform, metrics such as area utilization, delay, and power consumption have been evaluated. TinyJAMBU needs the smallest area (577 LUTs) and is fastest (4.20 ns), though at the cost of high power consumption (1033 mW). Romulus and ASCON have a balanced profile with low area, minimal power, and fast response times, making them ideal for embedded systems. On Raspberry Pi platform, performance has been assessed through RAM usage, CPU utilization, and execution time. TinyJAMBU has again emerged as the most memory- and time-efficient algorithm, while Romulus and ASCON have shown consistent, balanced behavior across all metrics. Based on the overall analysis, TinyJAMBU is the best suited for ultra-constrained environments prioritizing speed and low memory usage, whereas ASCON and Romulus are preferable for more general-purpose, energy-efficient IoT deployments. This work supports informed algorithm selection for secure, resource-aware embedded applications.

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Implementation of NIST Lightweight Cryptography Finalists on Raspberry Pi and FPGA for Resource Constraints Applications

  • 会议论文

  • 发表日期：

    2026年

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  • Sayan Tripathi,
  • Jhilam Jana,
  • Jaydeb Bhaumik

摘要

The growing need for secure and efficient implementations in resource-constrained devices, particularly for Internet of Things (IoT) applications, has accelerated the development of lightweight cryptographic algorithms. This study presents implementation of NIST Lightweight Cryptography (LWC) finalists on both FPGA (Artix-7) and Raspberry Pi platforms and their performances are evaluated as well as compared. On FPGA platform, metrics such as area utilization, delay, and power consumption have been evaluated. TinyJAMBU needs the smallest area (577 LUTs) and is fastest (4.20 ns), though at the cost of high power consumption (1033 mW). Romulus and ASCON have a balanced profile with low area, minimal power, and fast response times, making them ideal for embedded systems. On Raspberry Pi platform, performance has been assessed through RAM usage, CPU utilization, and execution time. TinyJAMBU has again emerged as the most memory- and time-efficient algorithm, while Romulus and ASCON have shown consistent, balanced behavior across all metrics. Based on the overall analysis, TinyJAMBU is the best suited for ultra-constrained environments prioritizing speed and low memory usage, whereas ASCON and Romulus are preferable for more general-purpose, energy-efficient IoT deployments. This work supports informed algorithm selection for secure, resource-aware embedded applications.