arXiv (Cornell University) · 2020 · 16 citations · 2 references
Privacy ProtectionEngineeringInformation PrivacyCovid-19Social MediaData ScienceDigital HealthData AnonymizationPublic HealthData ManagementGoogle SearchesAnonymization ProcessContact TracingAnonymization Process DescriptionVersion 1.0Covid-19 PandemicPrivacy IssueData PrivacyDisease SurveillancePrivacy AnonymityPrivacyEpidemiologyPrivacy PreservationAvailable DatasetBig Data
This report describes the aggregation and anonymization process applied to the initial version of COVID-19 Search Trends symptoms dataset (published at https://goo.gle/covid19symptomdataset on September 2, 2020), a publicly available dataset that shows aggregated, anonymized trends in Google searches for symptoms (and some related topics). The anonymization process is designed to protect the daily symptom search activity of every user with $\varepsilon$-differential privacy for $\varepsilon$ = 1.68.
2
Differentially Private SQL with Bounded User Contribution
Royce J Wilson, Celia Yuxin Zhang, William H. K. Lam et al. · SHILAP Revista de lepidopterología · 2020 · 104 citations · Full text