{"title":"PUF建模攻击:介绍和概述","authors":"U. Rührmair, J. Sölter","doi":"10.7873/DATE.2014.361","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":6550,"journal":{"name":"2014 Design, Automation & Test in Europe Conference & Exhibition (DATE)","volume":"1 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"91","resultStr":"{\"title\":\"PUF modeling attacks: An introduction and overview\",\"authors\":\"U. Rührmair, J. Sölter\",\"doi\":\"10.7873/DATE.2014.361\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":6550,\"journal\":{\"name\":\"2014 Design, Automation & Test in Europe Conference & Exhibition (DATE)\",\"volume\":\"1 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"91\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Design, Automation & Test in Europe Conference & Exhibition (DATE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7873/DATE.2014.361\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Design, Automation & Test in Europe Conference & Exhibition (DATE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7873/DATE.2014.361","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.