Papers › Smooth Sensitivity for Geo-Privacy
Smooth Sensitivity for Geo-Privacy
Yuting Liang, Ke Yi
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
Suppose each user i holds a private value xᵢ in some metric space (U, dist), and an untrusted data analyst wishes to compute ∑ᵢ f(xᵢ) for some function f : U →ℝ by asking each user to send in a privatized f(xᵢ). This is a fundamental problem in privacy-preserving population analytics, and the local model of differential privacy (LDP) is the predominant model under which the problem has been studied. However, LDP requires any two different xᵢ, x′ᵢ to be ε-distinguishable, which can be overly strong for geometric/numerical data. On the other hand, Geo-Privacy (GP) stipulates that the level of distinguishability be proportional to dist(xᵢ, xᵢ′), providing an attractive alternative notion of personal data privacy in a metric space. However, existing GP mechanisms for this problem, which add a uniform noise to either xᵢ or f(xᵢ), are not satisfactory. In this paper, we generalize the smooth sensitivity framework from Differential Privacy to Geo-Privacy, which allows us to add noise tailored to the hardness of the given instance. We provide definitions, mechanisms, and a generic procedure for computing the smooth sensitivity under GP equipped with a general metric. Then we present three applications: one-way and two-way threshold functions, and Gaussian kernel density estimation, to demonstrate the applicability and utility of our smooth sensitivity framework.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections