PPAD: privacy preserving group-based advertising in online social networks

Abstract

Services provided as free by Online Social Networks (OSN) come with privacy concerns. Users' information kept by OSN providers are vulnerable to the risk of being sold to the advertising firms. To protect user privacy, existing proposals utilize data encryption, which prevents the providers from monetizing users' information. Therefore, the providers would not be financially motivated to establish secure OSN designs based on users' data encryption. Addressing these problems, we propose the first Privacy Preserving Group-Based Advertising (PPAD) system that gives monetizing ability for the OSN providers. PPAD performs profile and advertisement matching without requiring the users or advertisers to be online, and is shown to be secure in the presence of honest but curious servers that are allowed to create fake users or advertisers. We also present advertisement accuracy metrics under various system parameters providing a range of security-accuracy trade-offs.