{"title":"基于神经网络的侧信道攻击与对抗","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":"{\"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}","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}
Neural Network-Based Side Channel Attacks and Countermeasures
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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