A new privacy-preserving web metering scheme using third-party-centric analytics

Abstract

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.