Efficient and Privacy-Preserving Ad Conversion for V2X-Assisted Proximity Marketing

Abstract

Vehicle-to-Everything (V2X) assisted proximity marketing is one of the most promising V2X services due to its huge potential, and has attracted a lot of research efforts recently. In proximity marketing, roadside merchants rely on third-party ad networks to target their advertisements to nearby vehicles or pedestrians with related interests, and pay ad networks according to some pricing mechanisms, such as cost per-view. It is therefore important for merchants to learn ad conversion rate (how much of their revenue can be attributed to proximity marketing) such that merchants can adjust their advertising strategy. For ad conversion, two-party private set intersection (PSI) technique has been widely adopted, where ad networks and merchants can jointly compute ad conversion rate without leaking sensitive customer information. However, state-of-art literature on PSI either assumes the involved two parties honestly follow the protocol or only tolerates limited adversarial behaviors. In this paper, we first design a novel and efficient PSI scheme that is secure in the presence of malicious adversaries, where two parties can arbitrarily deviate from the scheme. By integrating an efficient input certification mechanism into the designed PSI scheme, we propose a privacy-preserving ad conversion protocol for V2X-assisted proximity marketing, that can achieve input privacy, unlinkability, unforgeability, and output verifiability. Security analysis demonstrates that the proposed ad conversion protocol is secure under cryptographic assumptions. Finally, we show that the proposed ad conversion protocol outperforms the state-of-art approaches when considering both security strength and computation complexity.