Blockchain-based crowdsourcing for human intelligence tasks with dual fairness  

作　　者：Yihuai Liang Yan Li Byeong-Seok Shin 

机构地区：[1]School of Information Science and Technology,Southwest Jiaotong University,Chengdu 611756,China [2]Department of Electrical and Computer Engineering,Inha University,Incheon 22212,Republic of Korea

出　　处：《Blockchain(Research and Applications)》2024年第4期1-13,共13页区块链研究(英文)

基　　金：supported by grants from the National Research Foundation of Korea(NRF),funded by the Korean government(Grant Nos.NRF-2022R1A2B5B01001553 and NRF-2022R1A4A1033549);provided by an Institute of Information&Communications Technology Planning&Evaluation(IITP)grant,also funded by the Korean government(MSIT)under Grant No.RS-2022-00155915,for the project titled“Artificial Intelligence Convergence Innovation Hu-man Resources Development(Inha University).”

摘　　要：Human intelligence tasks(HITs),such as labeling images for machine learning,are widely utilized for crowdsourcing human knowledge.Centralized crowdsourcing platforms face challenges of a single point of failure and a lack of service transparency.Existing blockchain-based crowdsourcing approaches overlook the low scalability problem of permissionless blockchains or inconveniently rely on existing ground-truth data as the root of trust in evaluating the quality of workers’answers.We propose a blockchain-based crowdsourcing scheme for ensuring dual fairness(i.e.,preventing false reporting and free riding)and improving on-chain efficiency concerning on-chain storage and smart contract computation.The proposed scheme does not rely on trusted authorities but rather depends on a public blockchain to guarantee dual fairness.An efficient and publicly verifiable truth discovery scheme is designed based on majority voting and cryptographic accumulators.This truth discovery scheme aims at inferring ground truth from workers’answers.The ground truth is further utilized to estimate the quality of workers’answers.Additionally,a novel blockchain-based protocol is designed to further reduce on-chain costs while ensuring truthfulness.The scheme has O(n)complexity for both on-chain storage and smart contract computation,regardless of the number of questions,where𝑛denotes the number of workers.Formal security analysis is provided,and extensive experiments are conducted to evaluate its effectiveness and performance.

关 键 词：Crowdsourcing Dual fairness Blockchain Human intelligence task Truth discovery 

分 类 号：TN9[电子电信—信息与通信工程]