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Property 3.3 — the Net mechanism is ε-differentially private

Proved
PrivateRelease.NetMechanism.property_3_3

by mikedeng1 · Oct 7, 2026 · Mathlib 0df444a (Lean v4.33.1)

differential-privacyexponential-mechanismp2o-batch-pfp2bp2o-gran-per-chapterp2o-plan-paperp2o-v1query-release

Let XXX be a finite data universe, nnn an input size, Q\mathcal QQ a class of real-valued queries on databases, α\alphaα a real number and NNN a minimum α\alphaα-net for Q\mathcal QQ (the paper's Nα(C)N_\alpha(C)Nα​(C)), and suppose the Net mechanism's quality score q(z,D′)=−max⁡Q∈Q∣Q(z)−Q(D′)∣q(z,D')=-\max_{Q\in\mathcal Q}|Q(z)-Q(D')|q(z,D′)=−maxQ∈Q​∣Q(z)−Q(D′)∣ has positive sensitivity GSqGS_qGSq​ over NNN. Then for every ε>0\varepsilon>0ε>0 the Net mechanism with parameter ε\varepsilonε is ε\varepsilonε-differentially private:

Pr⁡[Net(z)∈S]≤eε Pr⁡[Net(z′)∈S]\Pr[\mathrm{Net}(z)\in S]\le e^{\varepsilon}\,\Pr[\mathrm{Net}(z')\in S]Pr[Net(z)∈S]≤eεPr[Net(z′)∈S]

for all inputs z,z′z,z'z,z′ differing in one entry and all sets SSS of output databases, and each output law is a probability distribution.

Together with the utility results that follow, this is the "private" half of the paper's main theorem.

Formalization Note Neighbours differ in exactly one entry. The hypothesis GSq>0GS_q>0GSq​>0 is where the exponential mechanism's formula is defined.

Preamble
import Mathlib
import Definitions.Def_PrivateRelease_NetMechanism_ExpMech
Formal statement
namespace PrivateRelease.NetMechanism

open MeasureTheory

/-- Property 3.3 (p. 8): the Net mechanism (run on a minimum α-net `N = N_α(C)`, with a quality
score of positive sensitivity) is ε-differentially private, and its output laws are probability
measures. -/
theorem property_3_3 {X : Type} [Fintype X] {n : ℕ} (QC : Set (Multiset X → ℝ)) (ε α : ℝ)
    (N : Finset (Database X)) (hN : IsMinNet QC α N) (hsens : 0 < netSens n QC N)
    (hε : 0 < ε) :
    PrivLearn.Generic.IsDP (netMech (n := n) QC ε N) ε ∧
      ∀ z : Fin n → X, IsProbabilityMeasure (netMech QC ε N z) := by sorry

end PrivateRelease.NetMechanism
Source
Blum, Ligett, Roth, A Learning Theory Approach to Non-Interactive Database Privacy, arXiv:1109.2229v1 (2011), p. 8, Property 3.3
Human review
  • Endorsed by Shuze Chen · Oct 8, 2026

    Confirmed by the moderator at approval.

  • Endorsed by mikedeng1 · Oct 8, 2026

    Confirmed by the mission captain (proposal self-audit).

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