论文标题
通过非单调响应量化增强强烈的PUF安全性
Enhancing Strong PUF Security with Non-monotonic Response Quantization
论文作者
论文摘要
强大的物理不元件功能（PUF）为资源约束设备提供了低成本身份验证原始的。但是，大多数强大的PUF架构可以通过学习算法有限的CRP来建模。在本文中，我们介绍了强PUF的非单调响应量化概念。响应不仅取决于哪个路径更快，还取决于到达信号之间的距离。我们的实验表明，由此产生的PUF提高了针对学习攻击的安全性。为了证明，我们在65 nm技术中设计并实施了基于非单调量化的环形振荡器的PUF。测量结果显示出几乎理想的均匀性和独特性，比0 C到50 C的温度范围内的位错误率为13.4％。
Strong physical unclonable functions (PUFs) provide a low-cost authentication primitive for resource constrained devices. However, most strong PUF architectures can be modeled through learning algorithms with a limited number of CRPs. In this paper, we introduce the concept of non-monotonic response quantization for strong PUFs. Responses depend not only on which path is faster, but also on the distance between the arriving signals. Our experiments show that the resulting PUF has increased security against learning attacks. To demonstrate, we designed and implemented a non-monotonically quantized ring-oscillator based PUF in 65 nm technology. Measurement results show nearly ideal uniformity and uniqueness, with bit error rate of 13.4% over the temperature range from 0 C to 50 C.
