一个新的保护隐私的网络计量方案,使用以第三方为中心的分析

Fahad Alarifi, M. Fernández
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引用次数: 1

摘要

广告网站服务器希望有一个网络计量方案,可以安全地产生准确的唯一用户数量,同时保护用户的隐私。为了在准确性和隐私性之间取得平衡,网络计量方案必须以保护隐私的方式收集用户数据。如果对用户进行了身份验证,则很容易确定唯一访问者的数量;然而,身份验证和隐私本质上是相互冲突的需求。本文提出了一种基于分析的网络计量方案,与以前的方案相比,该方案在提供“足够好”的准确结果的同时提高了隐私性。更准确地说,我们提出了一种通用的web计量方案,以保护隐私的方式安全地捕获用户数据,并研究了该方案可以实现的不同场景。描述了每个场景,概述了假设和技术。场景和底层技术可用于改进现有方案(如Google Analytics)的隐私性,同时保持准确的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new privacy-preserving web metering scheme using third-party-centric analytics
It is desirable for advertising webservers to have a web metering scheme that can securely produce accurate number of unique users while preserving users' privacy. To achieve such balance between accuracy and privacy, the web metering scheme has to collect data about users in a privacy-preserving manner. If users are authenticated, it is easy to determine the number of unique visitors; however, authentication and privacy are inherently conflicting requirements. This paper proposes an analytics-based web metering scheme that improves privacy while providing “good enough” accurate results, compared to previous schemes. More precisely, we propose a generic web metering scheme to securely capture data about users in a privacy-preserving manner, and study different scenarios in which the scheme can be implemented. Each scenario is described, outlining assumptions and techniques. The scenarios and underlying techniques can be used as improvements to the privacy of existing schemes (like Google Analytics) while maintaining accurate results.
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