Towards Privacy-Preserving User Targeting Service Systems

Abstract

User targeting has significant advantages for service providers, allowing them to present targeted services and ads. User targeting services typically rely on collecting user personal information, such as location, demographics, browsing history. However, collecting user personal information raises critical privacy concerns. Because the collected user personal information may be abused, e.g., a curious administrator could peek at the information, the information may be sell to other parties. In this thesis, we focus on privacy concerns of user targeting in advertising services and coupon delivery services.

In the first part of this thesis, we propose to explore a practical system enabling secure and efficient targeted mobile advertising services. We first propose our system design of privacy-preserving targeted mobile ad delivery. It allows the ad network to perform accurate targeting, while ensuring strong privacy protection for mobile users. We then propose efficient privacy-preserving billing schemes enabling the ad network to charge advertisers in a privacy-preserving manner.

In the second part of this thesis, we present our research on user privacy protection and vendor coupon protection in targeted coupon delivery services. We propose a practical system enabling secure and accurate targeted mobile coupon delivery services. It enables the secure delivery of targeted coupons to eligible users equipped with mobile devices, whose behavioral profiles accurately satisfy the targeting profile defined by the vendor. Our design well preserves user privacy, and further provides the strict security guarantee of vendor protection, by verifying user’s eligibility for a coupon without revealing the vendor’s targeting preference.

Date of Award	1 Jun 2017
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Cong WANG (Supervisor)