A Zero Auxiliary Knowledge Membership Inference Attack on Aggregate Location Data

arXiv:2406.18671v1 Announce Type: new
Abstract: Location data is frequently collected from populations and shared in aggregate form to guide policy and decision making. However, the prevalence of aggregated data also raises the privacy concern of membership inference attacks (MIAs). MIAs infer whether an individual's data contributed to the aggregate release. Although effective MIAs have been developed for aggregate location data, these require access to an extensive auxiliary dataset of individual traces over the same locations, which are collected from a …

arxiv attack attacks contributed cs.cr cs.lg data decision decision making guide knowledge location location data making policy privacy privacy concern shared