隐私和背景知识Privacy and Background Knowledge |
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课程网址: | http://videolectures.net/icml05_gehrke_pbk/ |
主讲教师: | Johannes Gehrke |
开课单位: | 康奈尔大学 |
开课时间: | 2007-02-25 |
课程语种: | 英语 |
中文简介: | 我们日常生活的数字化导致了政府,企业和个人收集数据的激增。保护这些数据的机密性至关重要。但是,私人数据统计属性的知识可以产生重大的社会效益,例如,基于人口普查数据的公共资金分配决策,或者分析来自不同医院的医疗数据以了解药物的相互作用。我将首先介绍两个应用场景,隐私保护数据分析和隐私保护数据发布。我将展示在简单模型中,背景知识如何导致两种应用程序中严重的隐私泄露,我将描述如何正确建模背景知识可以避免隐私泄露。我将概述用隐私保护数据分析和数据发布的第一个算法步骤和背景知识,我将以开放性问题作为结论。 |
课程简介: | The digitization of our daily lives has led to an explosion in the collection of data by governments, corporations, and individuals. Protection of confidentiality of this data is of utmost importance. However, knowledge of statistical properties of private data can have significant societal benefit, for example, in decisions about the allocation of public funds based on Census data, or in the analysis of medical data from different hospitals to understand the interaction of drugs. I will start by introducing two application scenarios, privacy-preserving data analysis and privacy-preserving data publishing. I will show how in simple models background knowledge can lead to severe breaches of privacy in both applications, and I will describe how proper modeling of background knowledge can avoid privacy breaches. I will outline first algorithmic steps towards privacy-preserving data analysis and data publishing with background knowledge, and I will conclude with open problems. |
关 键 词: | 数字化; 数据统计; 隐私保护数据分析 |
课程来源: | 视频讲座网 |
最后编审: | 2019-04-17:lxf |
阅读次数: | 49 |