Task matching in crowdsourcing is designed to provide convenient task information retrieval and has been extensively explored. In general, the task matching process is required to be reliable and to meet privacy requirements. However, most existing privacy-preserving task matching solutions for crowdsourcing focus on privacy issues but ignore the reliability of the process. In this paper, we propose a blockchainbased task matching scheme for crowdsourcing with a secure and reliable matching. Instead of utilizing a centralized cloud server, we employ smart contracts, an emerging blockchain technology, to provide reliable and transparent matching. In this way, data confidentiality and identity anonymity are achieved effectively and efficiently. The extensive privacy analysis and performance evaluation show that our solution is secure and feasible. INDEX TERMS Crowdsourcing, task matching, blockchain, smart contract, privacy-preserving.
Mobile crowdsensing (MCS) is an emerging data collection paradigm that exploits the potential of individual mobile devices to acquire mass data in a cost-effective manner. One of the important challenges in MCS application is to resist malicious users who provide false data to disturb the system. In the existing work, the reputation management scheme is an effective way to overcome the challenge. However, most reputation management schemes rely on a semi-honest server and process data in the plaintext domain without considering server security and user privacy. In this paper, we integrate the blockchain and edge computing in the MCS scenario to construct a credible and efficient blockchain-based MCS system, called BC-MCS. To resist malicious users, we present a privacy-preserving reputation management scheme based on the proposed system. Furthermore, we design a delegation protocol to solve the inherent problem of user dynamics in the MCS. The prototype system implemented on the Hyperledger Sawtooth and Android client demonstrates that our scheme can achieve higher utility and security levels in handling malicious users compared with the previous centralized reputation management schemes.INDEX TERMS Mobile crowdsensing, reputation management, privacy, blockchain, edge computing.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.