The Application of Blockchain Smart Contract Technology in the Prevention of Brush Order Behaviors in Recommendation Systems

Abstract

This paper is dedicated to addressing the management challenge of fake transaction behavior in recommendation systems and proposes a novel solution that integrates smart contracts and blockchain technology. By delving into the decentralized nature of blockchain, the immutability of its data, and the automatic execution advantages of smart contracts—especially the anonymous transaction environment provided by the latter—it not only effectively protects the personal privacy of participants but also reduces transaction biases caused by differences in identity, thereby promoting a more fair and transparent transaction process. Taking the anti-fake transaction mechanism of e-commerce platforms as an example, this paper demonstrates the significant effectiveness of this technological combination in enhancing data reliability, enabling dynamic rule adjustments, and facilitating cross-platform collaboration. The study finds that this method can reduce the false transaction detection omission rate by 30% to 50%, while also enhancing the fairness of the recommendation system and the level of user trust. In addition, the paper discusses potential future directions for technological integration, such as privacy computing and federated learning, and provides corresponding legal compliance recommendations.