RECO-LFSR:基于LFSR的可重构低功耗加密处理器,适用于可信物联网平台

Mohamed El-Hadedy, Russell Hua, Kazutomo Yoshii, Wen-mei W. Hwu, M. Margala
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引用次数: 0

摘要

今天,我们看到大量使用轻量级计算机硬件,特别是随着物联网设备在家庭中的使用越来越多。然而,这些设备往往忽视安全,直到为时已晚,敏感数据泄露发生。从这里开始,寻找轻量级加密原语来保护物联网设备的重要性呈指数级增长,同时不影响有限的资源和电池寿命的限制。在寻找轻量级加密标准时,必须考虑如何以最佳方式实现这些算法。例如,算法的某些部分在硬件上可能比在软件上快,反之亦然。本文提出了一个支持MicroBlaze软核处理器的硬件扩展,以有效地在Digilent Nexys A7-100T上实现轻量级加密(LWC)决赛(TinyJAMBU)之一。提出的硬件扩展包括一个可重构的非线性反馈移位寄存器(NLFSR),该寄存器是带关联数据的身份验证加密(AEAD) TinyJAMBU的中心计算部分。提出的NLFSR可以运行不同版本的TinyJAMBU,在100 MHz下仅在10分钟内消耗186mwh。在FPGA上托管提议的NLFSR所需的总资源为610 LUT和505 flip - flop,而可执行二进制大小减少了352字节。因此,提出的基于硬件扩展的解决方案比使用MicroBlaze实现整个TinyJAMBU的纯软件实现快x2.17倍,同时多消耗6兆瓦时。据我们所知,这是第一个在FPGA上使用软核处理器MicroBlaze的软硬件分区的TinyJAMBU实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RECO-LFSR: Reconfigurable Low-power Cryptographic processor based on LFSR for Trusted IoT platforms
Today we see lightweight computer hardware utilized in large volumes, especially with the growing use of IoT devices in homes. However, such devices often ignore security until it is too late and sensitive data breaches have occurred.From here, the importance of finding lightweight cryptographic primitives to secure IoT devices is exponentially increasing, while not impacting the limited resources and limitation of the battery lifetime. In the search for a lightweight cryptographic standard, one must consider how to implement such algorithms optimally. For example, certain parts of an algorithm might be faster in hardware than in software and vice versa.This paper presents a hardware extension supporting the MicroBlaze softcore processor to efficiently implement one of the Lightweight Cryptography (LWC) finalists (TinyJAMBU) on Digilent Nexys A7-100T. The proposed hardware extension consists of a reconfigurable Non-Linear Feedback Shift Register (NLFSR), the central computing part for the authenticated encryption with associated data (AEAD) TinyJAMBU. The proposed NLFSR can run different variants of TinyJAMBU while only consuming 186 mWh in just ten minutes at 100 MHz. The total resources needed to host the proposed NLFSR on the FPGA are 610 LUT and 505 Flip-Flops while executable the binary size is 352 bytes smaller. Therefore, the proposed solution based on the hardware extension is x2.17 times faster than the pure software implementation of the whole TinyJAMBU using MicroBlaze while consuming six mWh more. To our knowledge, this is the first implementation of TinyJAMBU using software/hardware partitioning on FPGA with the softcore processor MicroBlaze.
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