Area coverage-based worker recruitment under geo-indistinguishability

Location information is usually required for area coverage-based worker recruitment in mobile crowdsensing, which may pose considerable threats to individual privacy without proper privacy protection. In this paper, we investigate the problem of -based worker recruitment under geo-indistinguishability while considering each participant’s sensing radius, which aims to select a suitable set of participants under a worker number constraint to achieve the maximum coverage ratio for a target region. To this end, we present a geo-inditinguishable ara overage-based worke rcruitmen approach, referred to as . In , to protect each participant’s location, we develop an optimized geographical exponential mechanism with solid privacy and utility guarantees. To select the recruited workers based on the obfuscated locations while ensuring large coverage for the target region, we design a coverage-aware worker selection method . We show satisfies a discrete version of .