{"title":"Neural Network-Based Side Channel Attacks and Countermeasures","authors":"D. Serpanos, Shengqi Yang, M. Wolf","doi":"10.1109/DAC18072.2020.9218511","DOIUrl":null,"url":null,"abstract":"This paper surveys results in the use of neural networks and deep learning in two areas of hardware security: power attacks and physically-unclonable functions (PUFs).","PeriodicalId":428807,"journal":{"name":"2020 57th ACM/IEEE Design Automation Conference (DAC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 57th ACM/IEEE Design Automation Conference (DAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DAC18072.2020.9218511","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper surveys results in the use of neural networks and deep learning in two areas of hardware security: power attacks and physically-unclonable functions (PUFs).
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