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Cause Analysis Method of Entropy Loss in Physically Unclonable Functions

机译:物理不可克隆函数的熵损失原因分析方法

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The use of physically unclonable functions (PUFs) as a new cryptographic technique is gaining attention. Challenge-response authentication and key generation (key storage) are well known as major applications using PUFs. When PUFs are applied to these applications, min-entropy estimation is essential. The min-entropy is a measure of the lower bound of the unpredictability of PUF responses. Many studies have estimated the min-entropy of PUFs, and several of these studies dealt with PUFs with independent and identically distributed (IID) PUF responses. Few studies have focused on non-IID PUFs. One reason is that some causes of entropy loss are complicatedly intertwined, and the entropy estimation of non-IID PUFs is hard. Thus, it is first necessary to break down the intertwined causes to estimate min-entropy. In this paper, we present typical causes of entropy loss during PUF implementation and propose a cause analysis method using the Inter-Hamming distance (HD), which is one of major performance metrics of PUFs. And the proposed method was applied to prototyped PUFs designed with a 180-nm CMOS process. We demonstrate that the causes of entropy loss on each PUF can be broken down according to the analysis results.
机译:物理上不可克隆的功能(PUF)作为一种新的加密技术的使用正在引起人们的关注。质询-响应身份验证和密钥生成(密钥存储)是使用PUF的主要应用程序。当PUF应用于这些应用时,最小熵估计是必不可少的。最小熵是PUF响应不可预测性下限的度量。许多研究已经估计了PUF的最小熵,其中一些研究涉及具有独立且均匀分布(IID)PUF响应的PUF。很少有研究关注非IID PUF。原因之一是一些原因造成的熵损失复杂地交织在一起,并且非IID PUF的熵估计很困难。因此,首先有必要分解相互纠缠的原因以估计最小熵。在本文中,我们介绍了PUF实施过程中熵损失的典型原因,并提出了一种使用锤间距离(HD)的原因分析方法,该方法是PUF的主要性能指标之一。并将该方法应用于采用180 nm CMOS工艺设计的原型PUF。我们证明,根据分析结果,可以分解每个PUF上熵损失的原因。

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