Research map / Federated learning and privacy / Differential privacy
Differentially Private Gomory-Hu Trees
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Gives an epsilon-DP polynomial-time algorithm that outputs an approximate Gomory-Hu tree with tilde-O(n/eps) additive error for all-pairs min s-t cuts, via a new DP min isolating cuts primitive.
Problem
Releasing all-pairs minimum s-t cuts (APMC) in an undirected weighted graph under differential privacy with small additive error; prior bounds were O(n^{3/2}/eps) pure DP and sqrt(mn)/eps approximate DP.
Approach
Recursive Gomory-Hu construction (low-depth, Steiner-tree variant) where each min-isolating-cut step is privatized using a DP min s-t cut with penalty edges to a sink, a changing acceptance threshold across sampling levels, and noisy edges added to contracted instances so that each edge influences only one recursive branch, with budget split across levels.
Key results
- Epsilon-DP algorithm outputs approximate GH-tree with tilde-O(n/eps) additive error for all pairs s,t w.h.p., in tilde-O(n^2) time, improving prior O(n^{3/2}/eps) pure DP bound.
- New epsilon-DP min isolating cuts algorithm with tilde-O(n/eps) additive error.
- Corollaries: pure DP global min cut with tilde-O(n/eps) error in polynomial time, and minimum k-cut with multiplicative 2 and additive tilde-O(nk/eps) error.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use a pure-DP approximate Gomory-Hu tree instead of releasing a synthetic graph that preserves all cuts | APMC · APMC | additive error: O(n^{3/2}/\eps) -> \Tilde{O}(n/\eps) | Helped |
| Use a pure-DP approximate Gomory-Hu tree instead of the approximate-DP all-cuts algorithm | APMC · APMC | additive error: \tilde{O}(\sqrt{mn}/\eps) -> \Tilde{O}(n/\eps) | Helped |
| Introduce a private Min Isolating Cuts algorithm | Differentially private Gomory-Hu tree · Min Isolating Cuts | additive error: \tO(n/\eps) | Helped |
| Recover global Min Cut from the private Gomory-Hu tree | Differentially private Gomory-Hu tree · Global Min Cut | additive error: \tilde{O}(n/\eps) | Helped |
| Use the private Gomory-Hu tree to construct a minimum k-cut | Differentially private Gomory-Hu tree · Minimum k-cut | additive error: \tilde{O}(k^{1.5}/\eps) -> \tilde{O}(nk/\eps) | Mixed |
Surprising findings
- Pure-DP all-pairs min cut matches the tilde-O(n/eps) error of single-pair min cut up to polylog factors, closing the gap with synthetic-graph methods.
Limitations
- Error is tilde-O(n/eps) with polylog factors (up to lg^8 n in the approximate tree lemma), not tight in log factors
- Global min cut in polynomial time with pure DP and O(log n/eps) error remains open
- Releasing only cut values (not cuts) may admit better error; lower bound unknown
Experimental setup
Metrics: additive error of min s-t cut values approximation of Gomory-Hu tree
Baselines: Gupta-Roth-Ullman all-cuts synthetic graph (O(n^{3/2}/eps)) Liu-Upadhyay-Zou synthetic graph (sqrt(mn)/eps, approx DP) Laplace noise on all cut values (O(n/eps), approx DP)
Builds on: Gomory-Hu tree (Abboud et al. low-depth recursion) Dalirrooyfard et al. private min s-t cut Gupta-Roth-Ullman private cuts Isolating cuts lemma
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