WQCrowd: Secure blockchain-based crowdsourcing framework with multi-tier worker quality evaluation

Abstract

Crowdsourcing platforms play a crucial role in promoting transparency and collaborative engagement among participants while aiming to reduce resource consumption and costs. To achieve this, these platforms incorporate mechanisms for monitoring and evaluating worker quality performance. However, significant challenges persist. Centralized systems present trust issues due to their vulnerability to single-point failures. Moreover, data manipulation by malicious actors undermine confidence in the evaluation process, and biased assessments and reward distribution may lead to reduced worker motivation. Addressing these concerns necessitates the development of a decentralized system that ensures trustworthiness, tamper-resistance, accountability, reliability, transparency, and security. This paper introduces a secure multi-tier worker quality evaluation crowdsourcing framework based on blockchain technology. WQCrowd utilizes smart contracts and adopts a three-tier model comprising the Identity, Worker Activity, and Reputation tiers. Additionally, an automated game-based worker evaluation method is incorporated, enhancing the precision of performance assessments. Through our Proof of Concept (PoC) analysis, we demonstrate that the utilization of the blockchain system effectively addresses security concerns, including trust, privacy, and accountability, prevalent in current worker performance evaluation systems. Furthermore, the implementation of the game-based automated system enables our proposed solution to make informed decisions regarding worker quality performance evaluation.