BPTM: Blockchain-Based Privacy-Preserving Task Matching in Crowdsourcing

Abstract

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.

Blockchain from the Perspective of Privacy and Anonymisation: A Systematic Literature Review

“…Big Data. The approach taken in this area [ 23 , 45 , 47 ] with respect to the use of blockchain technology is to increase the level of confidentiality, especially of the information being shared. The fact of storing large amounts of information and combining this with blockchain technology presents the disadvantage of the capacity that can support each transaction, so storage off-chain appears as a solution, which in turn raises issues such as security and data privacy.…”

“…On the other hand, we find ETHEREUM [ 21 ] which provides other uses and applications for blockchain technology in addition to cryptocurrencies. Cryptocurrency technology is used for other purposes, such as smart contracts [ 45 ] and providing them with the necessary privacy and anonymity.…”

“…With regard to anonymisation, there is more controversy: the works in [31,32,[47][48][49] claim that total anonymity of the identities participating in the blockchain is not achieved and, on the other hand, the works in [9,40,41,[43][44][45][46]50,51] claim that it is. This issue raises concerns as different publications offer different approaches.…”

“…As can be seen in Figure 3 , there is a relationship between the terms privacy and anonymity in several of the studies analysed, finding that some only address privacy-related mechanisms [ 8 , 26 ] and that focuses solely on privacy, not on anonymity, addressing consensus mechanisms as a way of ensuring the privacy of transactions or through the elimination of central servers. We note that most studies selected for data extraction address both privacy and anonymity in conjunction and find an intrinsic relationship between the two terms [ 7 , 9 , 23 , 24 , 25 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 ].…”

TSWCrowd: A Decentralized Task-Select-Worker Framework on Blockchain for Spatial Crowdsourcing

“…It can be seen that due to the existence of a centralized platform, existing solutions cannot guarantee the correctness of the matching results. At present, most of the crowdsourcing models based on blockchain only allocate tasks according to workers' interest sets [32] [33], which is not a reliable task allocation method without ensuring the reliability of workers' information, that is, there are a large number of malicious workers in the system. [34] The task allocation scheme of the model is to allocate tasks according to the time sequence requested by workers, which does not guarantee the maximization of the rationality of workers' task allocation.…”