arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2602.04415cs.ARcs.CR
收藏

Crypto-RV:面向物联网安全的高效FPGA-based RISC-V加密协处理器

Crypto-RV: High-Efficiency FPGA-Based RISC-V Cryptographic Co-Processor for IoT Security

Nara Institute of Science and Technology(奈良先端科学技术大学院大学);University of Information Technology(信息工程大学);Vietnam National University(越南国立大学);Le Quy Don Technical University(黎贵敦技术大学)

Anh Kiet Pham, Van Truong Vo, Vu Trung Duong Le, Tuan Hai Vu, Hoai Luan Pham, Van Tinh Nguyen, Yasuhiko Nakashima

AI总结:

Crypto-RV是一种基于FPGA的RISC-V加密协处理器,通过统一支持多种加密算法,实现高效、低功耗的物联网安全加密处理。

摘要:

加密操作对于保障物联网、边缘计算和自主系统至关重要。然而,当前的RISC-V平台缺乏对全面加密算法家族和后量子密码学的高效硬件支持。本文提出了Crypto-RV,一种RISC-V协处理器架构,它在一个64位数据路径中统一支持SHA-256、SHA-512、SM3、SHA3-256、SHAKE-128、SHAKE-256、AES-128、HARAKA-256和HARAKA-512。Crypto-RV引入了三个关键的架构创新:高带宽的内部缓冲区(128x64位)、专为加密设计的执行单元(四阶段流水线数据路径)以及具有自适应调度的双缓冲机制,优化了大哈希处理。在Xilinx ZCU102 FPGA上以160 MHz频率运行,动态功耗为0.851 W,Crypto-RV在基准RISC-V核心上实现了165到1,061倍的速度提升,在与强大CPU相比,能量效率提高了5.8到17.4倍。该设计仅占用34,704个LUTs、37,329个FFs和22个BRAMs,证明了其在资源受限的物联网环境中的可行性,适用于高性能、低功耗的加密处理。

英文摘要:

Cryptographic operations are critical for securing IoT, edge computing, and autonomous systems. However, current RISC-V platforms lack efficient hardware support for comprehensive cryptographic algorithm families and post-quantum cryptography. This paper presents Crypto-RV, a RISC-V co-processor architecture that unifies support for SHA-256, SHA-512, SM3, SHA3-256, SHAKE-128, SHAKE-256 AES-128, HARAKA-256, and HARAKA-512 within a single 64-bit datapath. Crypto-RV introduces three key architectural innovations: a high-bandwidth internal buffer (128x64-bit), cryptography-specialized execution units with four-stage pipelined datapaths, and a double-buffering mechanism with adaptive scheduling optimized for large-hash. Implemented on Xilinx ZCU102 FPGA at 160 MHz with 0.851 W dynamic power, Crypto-RV achieves 165 times to 1,061 times speedup over baseline RISC-V cores, 5.8 times to 17.4 times better energy efficiency compared to powerful CPUs. The design occupies only 34,704 LUTs, 37,329 FFs, and 22 BRAMs demonstrating viability for high-performance, energy-efficient cryptographic processing in resource-constrained IoT environments.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑