CROWDFL: Privacy-preserving mobile crowdsensing system via federated learning

• Main Authors: ZHAO, Bowen, LIU, Ximeng, CHEN, Wei-Neng, DENG, Robert H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Crowdsensing; federated learning; homomorphic encryption; incentive; privacy protection; Information Security; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/8186
• Institution: Singapore Management University

As an emerging sensing data collection paradigm, mobile crowdsensing (MCS) enjoys good scalability and low deployment cost but raises privacy concerns. In this paper, we propose a privacy-preserving MCS system called CROWDFL by seamlessly integrating federated learning (FL) into MCS. At a high level...