{"title":"APUF Production Line Faults: Uniqueness and Testing","authors":"Y. Wei, Wenjing Rao, N. Devroye","doi":"10.23919/DATE56975.2023.10137226","DOIUrl":null,"url":null,"abstract":"Arbiter Physically Unclonable Functions (APUFs) are low-cost hardware security primitives that may serve as unique digital fingerprints for ICs. To fulfill this role, it is critical for manufacturers to ensure that a batch of PUFs coming off the same design and production line have different truth tables, and uniqueness / inter-PUF-distance metrics have been defined to measure this. This paper points out that a widely-used uniqueness metric fails to capture some special cases, which we remedy by proposing a modified uniqueness metric. We then look at two fundamental APUF-native production line fault models that severely affect uniqueness: the $\\mu$ (abnormal mean of a delay difference element) and (abnormal variance of a delay difference element) faults. We propose test and diagnosis methods aimed at these two APUF production line faults, and show that these low-cost techniques can efficiently and effectively detect such faults, and pinpoint the element of abnormality, without the (costly) need to directly measure the uniqueness metric of a PUF batch.","PeriodicalId":340349,"journal":{"name":"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/DATE56975.2023.10137226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Arbiter Physically Unclonable Functions (APUFs) are low-cost hardware security primitives that may serve as unique digital fingerprints for ICs. To fulfill this role, it is critical for manufacturers to ensure that a batch of PUFs coming off the same design and production line have different truth tables, and uniqueness / inter-PUF-distance metrics have been defined to measure this. This paper points out that a widely-used uniqueness metric fails to capture some special cases, which we remedy by proposing a modified uniqueness metric. We then look at two fundamental APUF-native production line fault models that severely affect uniqueness: the $\mu$ (abnormal mean of a delay difference element) and (abnormal variance of a delay difference element) faults. We propose test and diagnosis methods aimed at these two APUF production line faults, and show that these low-cost techniques can efficiently and effectively detect such faults, and pinpoint the element of abnormality, without the (costly) need to directly measure the uniqueness metric of a PUF batch.