论文标题
吸气：为物联网实现高性能和节能的SRAM加密哈希
Inhale: Enabling High-Performance and Energy-Efficient In-SRAM Cryptographic Hash for IoT
论文作者
论文摘要
在大数据时代，信息安全已成为辩论的主要问题，尤其是随着物联网（IoT）的兴起，攻击者可以毫不费力地获得对边缘设备的物理访问。哈希算法是当前的数据完整性和身份验证的基础。但是，在资源受限的边缘设备上提供高性能，高通量和节能解决方案是一项挑战。在本文中，我们提出了吸入式的SRAM体系结构，以有效地计算具有创新数据一致性和有效读取/写入策略的哈希算法，以通过原位控制器隐式执行数据转移操作。我们提出了吸入的两种变体：Inhale-opt，该变体针对潜伏期，吞吐量和跨越空间进行了优化；并吸入FLEX，它在重新利用哈希计算的最后一部分缓存方面具有灵活性。我们对SRAM和RERAM记忆的拟议架构进行了彻底评估，并将其与最先进的内存和ASIC加速器进行比较。我们的绩效评估证实，与先进的解决方案相比，吸气量可以达到1.4倍-14.5倍的吞吐量高点和大约两个型刻度的量度高点。
In the age of big data, information security has become a major issue of debate, especially with the rise of the Internet of Things (IoT), where attackers can effortlessly obtain physical access to edge devices. The hash algorithm is the current foundation for data integrity and authentication. However, it is challenging to provide a high-performance, high-throughput, and energy-efficient solution on resource-constrained edge devices. In this paper, we propose Inhale, an in-SRAM architecture to effectively compute hash algorithms with innovative data alignment and efficient read/write strategies to implicitly execute data shift operations through the in-situ controller. We present two variations of Inhale: Inhale-Opt, which is optimized for latency, throughput, and area-overhead; and Inhale-Flex, which offers flexibility in repurposing a part of last-level caches for hash computation. We thoroughly evaluate our proposed architectures on both SRAM and ReRAM memories and compare them with the state-of-the-art in-memory and ASIC accelerators. Our performance evaluation confirms that Inhale can achieve 1.4x - 14.5x higher throughput-per-area and about two-orders-of-magnitude higher throughput-per-area-per-energy compared to the state-of-the-art solutions.
