Privacy in context-aware mobile crowdsourcing systems

• Main Authors: KANDAPPU, Thivya, MISRA, Archan, CHENG, Shih-Fen, LAU, Hoong Chuin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Daily routines; Effective location; In contexts; Mobile crowdsourcing; Mobility traces; Privacy invasions; Push-based; User location; Perturbation techniques; Artificial Intelligence and Robotics; Information Security; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/3630; https://ink.library.smu.edu.sg/context/sis_research/article/4632/viewcontent/IEEE_certified_version.pdf
• Institution: Singapore Management University

Mobile crowd-sourcing can become as a strategy to perform time-sensitive urban tasks (such as municipal monitoring and last mile logistics) by effectively coordinating smartphone users. The success of the mobile crowd-sourcing platform depends mainly on its effectiveness in engaging crowd-workers, a...