AcCrowd: Blockchain-based Crowdsourcing with Worker Anonymity and Payment Correctness

Abstract

To improve the security of crowdsourcing, existing studies introduce blockchain to ensure reliability and utilize cryptography (e.g., encryption and zero-knowledge proof) to protect data privacy. Nevertheless, the crowdsourcing process may involve sensitive identity information, and identity protection remains unresolved during stages such as data submission and correct payment. Especially, when workers invoke a smart contract to submit data, it inevitably exposes their identities. Identity disclosure significantly impacts the credibility of crowdsourcing platforms. Existing solutions suggest solving the problem through anonymous token contracts such as Zether. However, tokens can easily result in fund freezing or extra information leakage. Moreover, invoking the contract to submit data will still disclose workers' blockchain accounts. To tackle the identity protection issue, in this paper, we propose AcCrowd which achieves worker anonymity and payment correctness in crowdsourcing systems atop blockchain. We first design a verifiable proxy submission mechanism for data submission, enabling workers to invoke contracts without disclosing their accounts. Then, we introduce and improve the BlockMaze architecture to replace previous anonymous token-based methods, enhancing privacy and flexibility. Besides, we designed a revealed payment mechanism that utilizes an adaptor signature to bind data reveal and reward payment together, simultaneously protecting the requester and worker. Our security and performance evaluations demonstrate the security and practicability of AcCrowd.