A practical system for privacy-aware targeted mobile advertising services

Jinghua Jiang, Yifeng Zheng, Zhenkui Shi, Xingliang Yuan, Xiaolin Gui, Cong Wang

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

With the prosperity of mobile application markets, mobile advertising is becoming an increasingly important economic force. In order to maximize revenue, ads are recommended to be delivered to potentially interested users, which requires user targeting, i.e., analyzing users' profiles and exploring users' interests. However, collecting user personal information for targeted mobile advertising services raises critical privacy concerns. Although some solutions like anonymization and obfuscation have been proposed for privacy-aware targeted advertising, they undesirably face the issues of security, efficiency, and/or ad relevance. In this paper, we propose a practical system enabling secure and efficient targeted mobile advertising services. It allows the ad network to perform accurate user targeting, while ensuring strong privacy protection for mobile users. Specifically, we show how to properly leverage a cryptographic primitive called private stream searching to support secure, accurate, and practical targeted mobile ad delivery. Moreover, we propose secure billing schemes to enable the ad network to charge advertisers in a privacy-preserving manner. The security strength of our system is thoroughly analyzed. Through extensive experiments, we show that our system achieves practical efficiency on mobile devices.

Original languageEnglish
Pages (from-to)410-424
Number of pages15
JournalIEEE Transactions on Services Computing
Volume13
Issue number3
DOIs
Publication statusPublished - May 2020
Externally publishedYes

Keywords

  • mobile computing
  • private ad billing
  • private ad delivery
  • Targeted mobile advertising services
  • user privacy

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