{"title":"APUF生产线故障:独特性和测试","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":"{\"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}","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}
APUF Production Line Faults: Uniqueness and Testing
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.