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Pipeline SWIFT query selection appears to use exact marginal errors

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Valutazione

Difficoltà
4/5
Tempo stimato
3-5 giorni
Idoneità per principianti
35/100
Tipo di issue
Bug
Chiarezza
Abbastanza chiara
Stato di attività
Ferma
Stack tecnologico
python
Ambito
data, security

Direzione di ricerca

Inizia in dpsynth/pipeline_transformations/swift.py tracciando compute_exact_marginals, compute_errors, il budget “Swift Select Queries” e swift.select_queries; confronta questo percorso con la logica di selezione di local discrete_mechanisms.swift. Esamina la draft PR #31 e considera completata la issue quando i punteggi di selezione sono protetti da un budget separato, la misurazione usa il budget rimanente e la diagnostica non pubblica errori esatti.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Problem

The scalable pipeline SWIFT path appears to use exact-error-driven query selection.

In dpsynth/pipeline_transformations/swift.py, the pipeline computes exact candidate marginals, converts them into errors with marginals_computations.compute_errors(...), requests a budget named Swift Select Queries, and then passes the errors into swift.select_queries(...).

However, the selection scores do not appear to be noised before swift.select_queries(...); noise is added only later to the selected marginal measurements.

Why this matters

The selected clique tree / selected workload is itself data-dependent output. Concretely, the junction-tree topology, the selected clique set, and (when diagnostics are enabled) the exact error scores are all released and all depend on exact high-order marginals. If selection is driven by exact marginal errors, the later noisy measurement step does not protect the information leaked by which queries were selected.

This is separate from the local discrete_mechanisms.swift path, which has its own score-noising logic (_compute_initial_errors adds noise funded by a dedicated selection budget). The issue here is the scalable pipeline transformation path, which has no equivalent noising step.

Local evidence

Reviewed at commit 18c2c951bd2923f889f6e3b2b757e01aaae398ee; re-verified still present at current main (91e9181) — the pipeline path still feeds unnoised errors from compute_errors into swift.select_queries.

Relevant lines in the current tree:

  • dpsynth/pipeline_transformations/swift.py: exact_marginals = marginals_computations.compute_exact_marginals(...)
  • dpsynth/pipeline_transformations/swift.py: errors = marginals_computations.compute_errors(...)
  • dpsynth/pipeline_transformations/swift.py: budget request named Swift Select Queries
  • dpsynth/pipeline_transformations/swift.py: return swift.select_queries(errors_dict, ...)
  • dpsynth/pipeline_transformations/swift.py: noise is added at the later Add noise to selected marginals stage
  • dpsynth/pipeline_transformations/marginals_computations.py: compute_errors(...) uses exact_vals from exact marginals

Possible fix

Account separately for selection and measurement. Add DP noise to the vector of SWIFT candidate error scores before clique-tree/query selection, and use the remaining measurement budget only for selected marginal measurement. Diagnostic output should avoid publishing exact errors.

Draft PR

I opened a draft fix here: https://github.com/google/dpsynth/pull/31

Lingua principale
Python
Stelle
32
Fork
13
Merge medio
1g 19h
PR unite (30g)
20

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