FairECom: Towards Proof of E-Commerce Fairness Against Price Discrimination

Tao Jiang, Xu Yuan, Qiong Cheng, Yulong Shen, Liangmin Wang, Jianfeng Ma

Abstract: Price discrimination has been empirically exposed where e-commercial platforms aim to gain additional profits by charging customers with different prices for the same product/service. This situation becomes even worse in nowadays’ Big Data era, giving the chance for service providers to leverage artificial intelligence technologies to have the deep analysis of personalized patterns, urgently calling for solutions to prevent such discriminated behaviors to protect customers’ rights. This article aims to defend against price discrimination by developing a secure and privacy-preserving solution, provable for e-commerce fairness. Using a newly designed cryptographic accumulator and public bulletin board, our system, called FairECom, allows an auditor (i.e., a customer or third-party auditor) to verify if customers are experiencing price discrimination. In particular, FairECom enables a customer to check if his payment to a product/service is identical to other customers through a privacy-preserving challenge-response protocol, for implementing the price transparency against discrimination. We implement a prototype using an Ethereum-based public bulletin board to conduct the system evaluation. Our evaluation indicates that FairECom can integrate with existing APIs provided by Ethereum and incur acceptable costs when deploying to the e-commercial systems.