Robustness against fraudulent activities of a blockchain-based online review system

Abstract

Fake reviews are a major problem in online consumer feedback systems that not only mislead people due to incorrect information but also damage the overall credibility of online businesses. Popular online review platforms have tried to overcome this problem through various strategies. However, most attempts end with vulnerabilities and untraceable results. We demonstrate how centralized online review systems are vulnerable to attacks. The blockchain-based online review system, which incorporates a token curated registry (TCR), is proposed in this work. Mathematical models are defined to analyze the capability to handle problems of centralized systems and the proposed framework. Additionally, we construct scenarios to demonstrate empirical results on fake review spam prevention. Our framework can discourage fraudsters by requiring costs and exposing their actions. Moreover, the system relies on the majority of users rather than a central authority. Furthermore, the proposed framework provides flexible and reasonable operation, and the community-driven environment provides more credible information, which is driven by customers’ decisions.