Cryptology ePrint Archive: Report 2021/115

Fast Strategies for the Implementation of SIKE Round 3 on ARM Cortex-M4

Mila Anastasova and Reza Azarderakhsh and Mehran Mozaffari Kermani

Abstract: Abstract The Supersingular Isogeny Key Encapsulation mechanism (SIKE) is the only post-quantum key encapsulation mechanism based on supersingular elliptic curves and isogenies between them. Despite the security of the protocol, unlike the rest of the NIST post-quantum algorithms, SIKE requires more number of clock cycles and hence does not provide competitive timing, energy and power consumption results. However, it is more attractive offering smallest public key sizes as well as ciphertext sizes, which taking into account the impact of the communication costs and storage of the keys could become as good fit for resource-constrained devices. In this work, we present the fastest practical implementation of SIKE, targeting the platform Cortex-M4 based on the ARMv7-M architecture. We performed our measurements on NIST recommended device based on STM32F407 microcontroller, for benchmarking the clock cycles, and on the target board Nucleo-F411RE, attached to X-NUCLEO-LPM01A (Power Shield), for measuring the power and energy consumption. The lower level finite field arithmetic and extension field operations play main role determining the efficiency of SIKE. Therefore, we mainly focus on those improvements and apply them to all NIST required security levels. Our SIKEp434 implementations for NIST security level 1 take about 850ms which is about 22.3% faster than the counterparts appeared in previous work. Moreover, our implementations are 21.9%, 19.7% and 19.5% faster for SIKEp503, SIKEp610 and SIKEp751 in comparison to the previously reported work for other NIST recommended security levels. Finally, we benchmark power and energy consumption and report the results for comparison.

Category / Keywords: implementation / Isogeny-based cryptography, SIKE, ARM Cortex-M4, Arithmetic

Date: received 31 Jan 2021

Contact author: razarderakhsh at fau edu,manastasova2017@fau edu

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Version: 20210201:072654 (All versions of this report)

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