PiCoDa: privacy-preserving smart coupon delivery architecture

Abstract

In this paper, we propose a new privacy-preserving smart coupon delivery system called PiCoDa. Like prior work on private behavioral targeted advertising, PiCoDa protects user data by performing targeting on the end-users device. However, PiCoDa makes two more guarantees: it verifies a users eligibility for a coupon, and it protects the vendors privacy by not revealing the targeting strategy. To accommodate the constraints of different targeting strategies, PiCoDa provides two targeting protocols that tradeoff user privacy and vendor privacy in different ways. We show how both designs meet requirements for user privacy, vendor protection, and robustness. In addition, we present simulation results of the protocols using realistic parameters to further validate the efficiency and effectiveness of PiCoDa.