论文标题
有效地绑定了IID之外的物理不倾销功能的有条件最小室内
Efficient Bound for Conditional Min-Entropy of Physical Unclonable Functions Beyond IID
论文作者
论文摘要
通常在独立且相同分布的PUF响应的假设下估计由模糊提取从物理不封函数中提取的秘密的剩余最小渗透，但是在实践中不存在此假设。这项工作分析了响应是独立但不一定分布相同的更现实的情况。在这种情况下，我们扩展了Delvaux等人的（N-K）结合和更紧密的结合。特别是，我们建议进行分组结合，该界限为准确性与计算工作提供了权衡。与以前的界限进行比较显示了我们界限的准确性和效率。我们还根据来自Real Hartware的公开可用的PUF数据来调整关键排名（从侧通道分析中的工具），以交叉估算最先进的ART和我们提出的最小值范围。
The remaining min-entropy of a secret generated by fuzzy extraction from a Physical Unclonable Function is typically estimated under the assumption of independent and identically distributed PUF responses, but this assumption does not hold in practice. This work analyzes the more realistic case that the responses are independent but not necessarily identically distributed. For this case, we extend the (n-k) bound and a tighter bound by Delvaux et al. In particular, we suggest a grouping bound which provides a trade off for accuracy vs computational effort. Comparison to previous bounds shows the accuracy and efficiency of our bound. We also adapt the key rank (a tool from side-channel analysis) to cross-validate the state-of-the-art and our proposed min-entropy bounds based on publicly available PUF data from real hardware.
