Towards a memristive hardware secure hash function (MemHash)

Leonid Azriel, Shahar Kvatinsky
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引用次数: 9

Abstract

Hardware based hash functions might provide a low cost and low power alternative to the classic solutions, which are based on implementations of mathematical cryptographic algorithms. In this paper, we propose MemHash, a hardware secure hash function built using memristive technology that exploits the unique properties of memristors. The MemHash operation is based on intrinsic device characteristics. Furthermore, it exploits process variations for implicit key embedding, thus creating a keyed-hash message authentication code (HMAC) that does not involve a separate key generation and management process. MemHash comprises a memristive crossbar with a differential read mechanism and a scrambler unit. The scrambler unit receives the input message as a bit stream and digitally mixes it with data read from the array. For every bit of the message, the scrambler generates a write address and a value to perform a single-cell write cycle to the crossbar. Because the crossbar is designed to be extremely sensitive to the write disturb phenomenon, every single-cell write alters additional cells in the design, thus increasing the entropy. The differential read mechanism provides sensitivity to process variations and robustness in operating conditions, yielding a PUF-like effect. MemHash is evaluated with a 16 × 16 memristive crossbar structure. Our simulation results demonstrate the statistical characteristics of the proposed design, showing close-to-optimal uniqueness and diffuseness.
一种记忆硬件安全哈希函数(MemHash)
基于硬件的哈希函数可能为基于数学加密算法实现的经典解决方案提供低成本和低功耗的替代方案。在本文中,我们提出了MemHash,这是一个使用忆阻技术构建的硬件安全哈希函数,该技术利用了忆阻器的独特特性。MemHash操作基于设备的固有特性。此外,它利用隐式密钥嵌入的过程变化,从而创建一个不涉及单独的密钥生成和管理过程的密钥哈希消息身份验证代码(HMAC)。MemHash包括具有差动读取机制的忆阻交叉杆和扰频器单元。扰频器单元接收作为位流的输入消息,并将其与从阵列读取的数据进行数字混合。对于消息的每个位,扰频器生成一个写地址和一个值,以执行对交叉条的单单元写周期。由于横杆被设计为对写入干扰现象极其敏感,每一个单细胞写入都会改变设计中的其他细胞,从而增加熵。差分读取机制提供了对工艺变化的敏感性和在操作条件下的稳健性,产生了类似puf的效果。MemHash是用一个16 × 16的记忆交叉结构来求值的。仿真结果证明了所提设计的统计特性,具有接近最优的唯一性和扩散性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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