CrowdFA: A privacy-preserving mobile crowdsensing paradigm via federated analytics

• Main Authors: ZHAO, Bowen, LI, Xiaoguo, LIU, Ximeng, PEI, Qingqi, LI, Yingjiu, DENG, Robert H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Crowdsensing;privacy protection;data aggre-gation;reward distribution;federated analytics; Information Security; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/8226; https://ink.library.smu.edu.sg/context/sis_research/article/9229/viewcontent/CrowdFA_av.pdf
• Institution: Singapore Management University

Mobile crowdsensing (MCS) systems typically struggle to address the challenge of data aggregation, incentive design, and privacy protection, simultaneously. However, existing solutions usually focus on one or, at most, two of these issues. To this end, this paper presents CROWD FA, a novel paradigm...