CityOS is an edge runtime that enforces a three-tier privacy API for urban sensors: local raw data, differentially private single-location stats, and cross-location aggregates with per-user budgets enforced on devices.
Title resolution pending
4 Pith papers cite this work, alongside 7 external citations. Polarity classification is still indexing.
4
Pith papers citing it
7
external citations · external index
citation-role summary
background 2
citation-polarity summary
years
2026 4verdicts
UNVERDICTED 4roles
background 2polarities
background 2representative citing papers
Predictability is defined as incremental predictive gain for attackers with partial dataset knowledge; it is incomparable to DP in general but implies mutual-information DP in the worst case of one uncompromised individual and all binary queries, with a GMM-based asymptotic analysis yielding a calib
DP4SQL enables customizable differentially private SQL for relational databases by supporting flexible policies for record existence, contents, partially public data, and varying protection levels across data parts.
A differentially private pipeline using node-level DP summaries to fit ERGMs or SBMs, generate synthetic networks, and simulate SIS disease spread on ARTNet sexual contact data produces incidence, prevalence, and intervention effect sizes close to non-private versions.
citing papers explorer
-
CityOS: Privacy Architecture for Urban Sensing
CityOS is an edge runtime that enforces a three-tier privacy API for urban sensors: local raw data, differentially private single-location stats, and cross-location aggregates with per-user budgets enforced on devices.
-
Predictability as a Fine-Grained Measure for Privacy
Predictability is defined as incremental predictive gain for attackers with partial dataset knowledge; it is incomparable to DP in general but implies mutual-information DP in the worst case of one uncompromised individual and all binary queries, with a GMM-based asymptotic analysis yielding a calib
-
DP4SQL: Differentially Private SQL with Flexible Privacy Policies
DP4SQL enables customizable differentially private SQL for relational databases by supporting flexible policies for record existence, contents, partially public data, and varying protection levels across data parts.
-
Differentially Private Modeling of Disease Transmission within Human Contact Networks
A differentially private pipeline using node-level DP summaries to fit ERGMs or SBMs, generate synthetic networks, and simulate SIS disease spread on ARTNet sexual contact data produces incidence, prevalence, and intervention effect sizes close to non-private versions.