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Efficient Helper Data Key Extractor on FPGAs

机译:FPGA上的高效Helper数据密钥提取器

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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:物理不可克隆功能(PUF)的属性使它们对于各种与安全相关的应用程序非常有吸引力。由于它们固有地依赖于包含它们的设备的物理属性,因此可以将它们用于将应用程序唯一绑定到特定设备,以进行IP保护。这对于保护FPGA应用程序免受非法复制和分发至关重要。为了利用PUF的物理性质进行可靠的加密,使用所谓的辅助数据算法或模糊提取器从嘈杂的和不均匀的随机PUF响应中生成具有适当熵的加密密钥。在本文中,我们首次提出了FPGA上模糊提取器的高效实现方式,其中根据所需的硬件资源来衡量效率。这填补了完整的FPGA IP保护解决方案所缺少的构建块的空白。此外,在这种情况下,我们为Reed-Muller和Golay码的解码器提出了新的体系结构,并表明从面积和纠错能力的角度来看,我们的解决方案都非常有吸引力。

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