Towards Privacy-Preserving User Targeting

User targeting via behavioral analysis is becoming increasingly prevalent in online messaging services. By taking into account users' behavior information such as geographic locations, purchase behaviors, and search histories, vendors can deliver messages to users who are more likely to have a strong preference. For example, advertisers can rely on some ad-network for distributing ads to targeted users. However, collecting such personal information for accurate targeting raises severe privacy concerns. In order to incentivize users to participate in such behavioral targeting systems, addressing the privacy concerns becomes of paramount importance. We provide a survey of privacy-preserving user targeting. We present the architectures of user targeting, the security threats faced by user targeting, and existing approaches to privacy-preserving user targeting. Some future research directions are also identified.