通信学报2025，Vol.46Issue(5)：115-132,18.DOI:10.11959/j.issn.1000-436x.2025090
面向众包的隐私保护任务匹配方案
Privacy-preserving task matching scheme for crowdsourcing
摘要
Abstract
Crowdsourcing has become a crucial paradigm for task execution and data collection,with task matching serv-ing as a fundamental application.Due to the potential untrustworthiness of crowdsourcing platforms,which may lead to the leakage of users'private information,users are required to encrypt their data prior to uploading.To fulfill task match-ing while preserving privacy,the crowdsourcing platform employs encrypted spatial keyword queries to perform task matching of workers'interests and locations.To achieve secure and efficient crowdsourcing task matching,a privacy-preserving spatial keyword similarity-based task matching(SKSTM)scheme for crowdsourcing was proposed.SKSTM encoded locations and keywords by using the Geohash algorithm and bitmap representation,transforming spatial key-word similarity search into inner product calculations.Security analysis and experimental results demonstrate that SKSTM outperforms state-of-the-art schemes in task matching while effectively preserving the privacy of both task re-questers and workers.关键词
众包/任务匹配/相似性查询/隐私保护Key words
crowdsourcing/task matching/similarity search/privacy protection分类
计算机与自动化引用本文复制引用
宋甫元,丁思洋,王威,姜琴,付章杰..面向众包的隐私保护任务匹配方案[J].通信学报,2025,46(5):115-132,18.基金项目
国家自然科学基金资助项目(No.62302230,No.62302229,No.U22B2062) （No.62302230,No.62302229,No.U22B2062）
中国博士后科学基金资助项目(No.2024M751480)The National Natural Science Foundation of China(No.62302230,No.62302229,No.U22B2062)),China Post-doctoral Science Foundation(No.2024M751480) （No.2024M751480）
