Reliable and Streaming Truth Discovery in Blockchain-based Crowdsourcing
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Reliable and Streaming Truth Discovery in Blockchain-based Crowdsourcing. / Mukkamala, Prasanna Siddharth; Wu, Haiqin; Dudder, Boris.
2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2023. IEEE Computer Society Press, 2023. p. 492-500.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Reliable and Streaming Truth Discovery in Blockchain-based Crowdsourcing
AU - Mukkamala, Prasanna Siddharth
AU - Wu, Haiqin
AU - Dudder, Boris
N1 - Publisher Copyright: © 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Truth discovery is an effective and compelling approach to addressing data conflicts among different workers and offers more trustworthy truths to task requesters in crowdsourcing. Prior research either focused on studying more accurate truth discovery algorithms or aimed to protect data privacy from the centralized and honest-but-curious crowdsourcing platforms. They all overlooked the stronger threats from the malicious crowdsourcing platform (e.g., may return incorrectly estimated truths) and many critical issues inherited from centralization. This paper proposes a blockchain-based decentralized truth discovery scheme for crowdsourcing, with computation integrity guarantees against malicious participants and support for efficient processing of generic streaming data. We adopt the idea of hybrid storage and computations to ease the expensive on-chain cost. Workers are grouped for off-chain partial truth estimation and smart contracts are leveraged for on-chain final truth aggregation. To prevent any improper computations from malicious entities, we record the hashes of data and worker weights on-chain occasionally. Through theoretical analysis and extensive experiments over real-world and synthetic datasets implemented in Ethereum, we demonstrate that our scheme 1) achieves our reliability goals with certain privacy assurance; 2) exhibits a higher truth estimation accuracy than existing approaches and a lower gas consumption than the baseline.
AB - Truth discovery is an effective and compelling approach to addressing data conflicts among different workers and offers more trustworthy truths to task requesters in crowdsourcing. Prior research either focused on studying more accurate truth discovery algorithms or aimed to protect data privacy from the centralized and honest-but-curious crowdsourcing platforms. They all overlooked the stronger threats from the malicious crowdsourcing platform (e.g., may return incorrectly estimated truths) and many critical issues inherited from centralization. This paper proposes a blockchain-based decentralized truth discovery scheme for crowdsourcing, with computation integrity guarantees against malicious participants and support for efficient processing of generic streaming data. We adopt the idea of hybrid storage and computations to ease the expensive on-chain cost. Workers are grouped for off-chain partial truth estimation and smart contracts are leveraged for on-chain final truth aggregation. To prevent any improper computations from malicious entities, we record the hashes of data and worker weights on-chain occasionally. Through theoretical analysis and extensive experiments over real-world and synthetic datasets implemented in Ethereum, we demonstrate that our scheme 1) achieves our reliability goals with certain privacy assurance; 2) exhibits a higher truth estimation accuracy than existing approaches and a lower gas consumption than the baseline.
KW - blockchain
KW - crowdsourcing
KW - data stream
KW - reliability
KW - Truth discovery
UR - http://www.scopus.com/inward/record.url?scp=85177454688&partnerID=8YFLogxK
U2 - 10.1109/SECON58729.2023.10287465
DO - 10.1109/SECON58729.2023.10287465
M3 - Article in proceedings
AN - SCOPUS:85177454688
SP - 492
EP - 500
BT - 2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2023
PB - IEEE Computer Society Press
T2 - 20th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2023
Y2 - 11 September 2023 through 14 September 2023
ER -
ID: 374649263