PUF建模攻击:介绍和概述

U. Rührmair, J. Sölter
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引用次数: 91

摘要

基于机器学习(ML)的建模攻击是目前所谓的强物理不可克隆函数(Strong puf)最相关和最有效的攻击形式。本文对该方法进行了概述:讨论了(1)该方法适用的基本条件;(ii)在这种情况下使用的ML算法;(三)最新、最先进的成果;(iv)对现有结果的正确解释;(五)未来可能的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PUF modeling attacks: An introduction and overview
Machine learning (ML) based modeling attacks are the currently most relevant and effective attack form for so-called Strong Physical Unclonable Functions (Strong PUFs). We provide an overview of this method in this paper: We discuss (i) the basic conditions under which it is applicable; (ii) the ML algorithms that have been used in this context; (iii) the latest and most advanced results; (iv) the right interpretation of existing results; and (v) possible future research directions.
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