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CrISA-X: Unleashing Performance Excellence in Lightweight Symmetric Cryptography for Extendable and Deeply Embedded Processors

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Authors:
Oren Ganon
Itamar Levi
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DOI: 10.46586/tches.v2024.i3.377-417
URL: https://tches.iacr.org/index.php/TCHES/article/view/11682
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Abstract: The efficient execution of a Lightweight Cryptography (LWC) algorithm is essential for edge computing platforms. Dedicated Instruction Set Extensions (ISEs) are often included for this purpose. We propose the CrISA-X-a Cryptography Instruction Set Architecture eXtensions designed to improve cryptographic latency on extendable processors. CrISA-X, provides enhanced speed of various algorithms simultaneously while optimizing ISA adaptability, a feat yet to be accomplished. The extension, diverse for several computation levels, is first tailored explicitly for individual algorithms and sets of LWC algorithms, depending on performance, frequency, and area trade-offs. By diligently applying the Min-Max optimization technique, we have configured these extensions to achieve a delicate balance between performance, area utilization, code size, etc. Our study presents empirical evidence of the performance enhancement achieved on a synthesis modular RISC processor. We offer a framework for creating optimized processor hardware and ISA extensions. The CrISA-X outperforms ISA extensions by delivering significant performance boosts between 3x to 17x while experiencing a relative area cost increase of +12% and +47% in LUTs. Notably, as one important example, the utilization of the ASCON algorithm yields a 10x performance boost in contrast to the base ISA instruction implementation.
BibTeX
@article{tches-2024-34446,
  title={CrISA-X: Unleashing Performance Excellence in Lightweight Symmetric Cryptography for Extendable and Deeply Embedded Processors},
  journal={IACR Transactions on Cryptographic Hardware and Embedded Systems},
  publisher={Ruhr-Universität Bochum},
  volume={2024},
  pages={377-417},
  url={https://tches.iacr.org/index.php/TCHES/article/view/11682},
  doi={10.46586/tches.v2024.i3.377-417},
  author={Oren Ganon and Itamar Levi},
  year=2024
}