{"title":"MC2: A Secure Collaborative Computation Platform","authors":"R. A. Popa","doi":"10.1145/3411501.3418609","DOIUrl":null,"url":null,"abstract":"Multiple organizations often wish to aggregate their sensitive data and learn from it, but they cannot do so because they cannot share their data. For example, banks wish to train models jointly over their aggregate transaction data to detect money launderers because criminals hide their traces across different banks. To address such problems, my students and I developed MC2, a framework for secure collaborative computation. My talk will overview our MC2 platform, from the technical approach to results and adoption. Biography: Raluca Ada Popa is a computer security professor at UC Berkeley. She is a co-founder and co-director of the RISELab at UC Berkeley, where her research is on systems security and applied cryptography. She is also a co-founder and CTO of a cybersecurity startup called PreVeil. Raluca has received her PhD in computer science as well as her Masters and two BS degrees, in computer science and in mathematics, from MIT. She is the recipient of a Sloan Foundation Fellowship award, NSF Career, Technology Review 35 Innovators under 35, and a George M. Sprowls Award for best MIT CS doctoral thesis.","PeriodicalId":116231,"journal":{"name":"Proceedings of the 2020 Workshop on Privacy-Preserving Machine Learning in Practice","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 Workshop on Privacy-Preserving Machine Learning in Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3411501.3418609","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
Multiple organizations often wish to aggregate their sensitive data and learn from it, but they cannot do so because they cannot share their data. For example, banks wish to train models jointly over their aggregate transaction data to detect money launderers because criminals hide their traces across different banks. To address such problems, my students and I developed MC2, a framework for secure collaborative computation. My talk will overview our MC2 platform, from the technical approach to results and adoption. Biography: Raluca Ada Popa is a computer security professor at UC Berkeley. She is a co-founder and co-director of the RISELab at UC Berkeley, where her research is on systems security and applied cryptography. She is also a co-founder and CTO of a cybersecurity startup called PreVeil. Raluca has received her PhD in computer science as well as her Masters and two BS degrees, in computer science and in mathematics, from MIT. She is the recipient of a Sloan Foundation Fellowship award, NSF Career, Technology Review 35 Innovators under 35, and a George M. Sprowls Award for best MIT CS doctoral thesis.
多个组织经常希望聚合它们的敏感数据并从中学习,但是它们不能这样做,因为它们不能共享数据。例如,银行希望在他们的总交易数据上联合训练模型,以检测洗钱者,因为犯罪分子会在不同的银行隐藏他们的踪迹。为了解决这些问题,我和我的学生开发了MC2,一个安全协作计算的框架。我的演讲将概述我们的MC2平台,从技术方法到结果和采用。简介:Raluca Ada Popa是加州大学伯克利分校的计算机安全教授。她是加州大学伯克利分校RISELab的联合创始人和联合主任,她的研究方向是系统安全和应用密码学。她还是网络安全初创公司PreVeil的联合创始人兼首席技术官。Raluca在麻省理工学院获得了计算机科学博士学位、硕士学位和两个学士学位,分别是计算机科学和数学。她是斯隆基金会奖学金奖、美国国家科学基金会职业奖、技术评论35名35岁以下创新者奖和麻省理工学院最佳计算机科学博士论文奖的获得者。