{"title":"Short Paper: Device- and Locality-Specific Fingerprinting of Shared NISQ Quantum Computers","authors":"Mi Allen, Deng Shuwen, Szefer Jakub","doi":"10.1145/3505253.3505261","DOIUrl":null,"url":null,"abstract":"Fingerprinting of quantum computer devices is a new threat that poses a challenge to shared, cloud-based quantum computers. Fingerprinting can allow adversaries to map quantum computer infras-tructures, uniquely identify cloud-based devices which otherwise have no public identifiers, and it can assist other adversarial attacks. This work shows idle tomography-based fingerprinting method based on crosstalk-induced errors in NISQ quantum computers. The device- and locality-specific fingerprinting results show prediction accuracy values of 99 . 1% and 95 . 3%, respectively.","PeriodicalId":342645,"journal":{"name":"Workshop on Hardware and Architectural Support for Security and Privacy","volume":"421 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Hardware and Architectural Support for Security and Privacy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3505253.3505261","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Fingerprinting of quantum computer devices is a new threat that poses a challenge to shared, cloud-based quantum computers. Fingerprinting can allow adversaries to map quantum computer infras-tructures, uniquely identify cloud-based devices which otherwise have no public identifiers, and it can assist other adversarial attacks. This work shows idle tomography-based fingerprinting method based on crosstalk-induced errors in NISQ quantum computers. The device- and locality-specific fingerprinting results show prediction accuracy values of 99 . 1% and 95 . 3%, respectively.
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