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Efficient Helper Data Key Extractor on FPGAs

机译:高效的助手数据密钥提取器在FPGA上

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摘要

Physical Unclonable Functions (PUFs) have properties that make them very attractive for a variety of security-related applications. Due to their inherent dependency on the physical properties of the device that contains them, they can be used to uniquely bind an application to a particular device for the purpose of IP protection. This is crucial for the protection of FPGA applications against illegal copying and distribution. In order to exploit the physical nature of PUFs for reliable cryptography a so-called helper data algorithm or fuzzy extractor is used to generate cryptographic keys with appropriate entropy from noisy and non-uniform random PUF responses. In this paper we present for the first time efficient implementations of fuzzy extractors on FPGAs where the efficiency is measured in terms of required hardware resources. This fills the gap of the missing building block for a full FPGA IP protection solution. Moreover, in this context we propose new architectures for the decoders of Reed-Muller and Golay codes, and show that our solutions are very attractive from both the area and error correction capability points of view.
机译:物理不可渗透的函数(PUF)具有使它们对各种与安全相关的应用程序非常有吸引力的属性。由于它们对包含它们的设备的物理属性的固有依赖性,它们可用于唯一地将应用程序绑定到特定设备以获取IP保护的目的。这对于保护FPGA申请免于非法复制和分配至关重要。为了利用可靠加密的PUF的物理性质,使用所谓的帮助程序数据算法或模糊提取器来生成具有来自嘈杂和非均匀随机PUF响应的适当熵的加密密钥。在本文中,我们在FPGA上首次有效的模糊提取器的实现,其中效率是以所需的硬件资源测量。这填充了全FPGA IP保护解决方案的缺失构建块的间隙。此外,在此上下文中,我们为Reed-Muller和Golay代码的解码方式提出了新的架构,并表明我们的解决方案与区域和纠错能力的视图非常有吸引力。

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