An Implementation of Fake News Prevention by Blockchain and Entropy-based Incentive Mechanism

Abstract

Fake news is undoubtedly a significant threat to democratic countries nowadays because existing technologies can quickly and massively produce fake videos, articles, or social media messages based on the rapid development of artificial intelligence and deep learning. Therefore, human assistance is critical if current fake news prevention systems desire to improve accuracy. Given this situation, prior research has proposed to add a quorum, a group of appraisers trusted by users to verify the authenticity of digital content, to the fake news prevention systems. This paper proposes an Entropy-based incentive mechanism to diminish the negative effect of malicious behaviors on a quorum-based fake news prevention system. In order to maintain the Safety and Liveness of our system, we employed Entropy to measure the degree of voting disagreement to determine appropriate rewards and penalties. Moreover, we use Hyperledger Fabric, Schnorr signatures, and human appraisers to implement a practical prototype of a quorum-based fake news prevention system. Then we conduct necessary case analyses and experiments to realize how dishonest participants, crash failures, and scale impact our system. The outcomes of the case analyses and experiments show that our mechanisms are feasible and provide an analytical basis for developing fake news prevention systems. Furthermore, we have added six innovative contributions in this extension work compared to our previous workshop paper in DEVIANCE 2021.