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Claude
006a66ca20
Adds an `optimize` module that replaces the hand-picked shield config with a
derived, robustness-verified optimum, and hardens the experiment so the
collapse is proven to be signal-level, not classifier-level.
Model changes:
- throughput.rs: add a feedback-airtime term (cost rises with feedback bits)
alongside the falling quantization residual, giving a genuine interior
throughput optimum in feedback resolution.
- attacker.rs: add a selectable distance metric (Euclidean + Cosine) so the
optimizer can require the collapse to hold under multiple classifiers.
- experiment.rs: thread the attacker metric through; build the channel once.
optimize.rs:
- optimal_feedback_bits / spec_optimal_feedback_bits: throughput-best resolution
(3 bits unconstrained, matching DySPAN-2026; 5 bits within the 802.11 {5,7,9}
set).
- min_givens_passes: smallest mixing budget that collapses re-ID robustly across
both metrics AND N in {16,32}.
- pareto_frontier and hyper_optimize.
Findings and adopted defaults:
- Proven-minimum robust passes = 48; the hand-picked 112 was 2.3x over-
provisioned. Rotation mixing is keyed (never signaled), so extra passes are
throughput-free -> ship 96 (2x margin).
- Feedback resolution 5 bits (spec-optimal), down from 7.
- ShieldConfig::default() now equals hyper_optimize()'s output; a test guards
against drift.
Net vs. the original: strictly better on BOTH privacy and throughput.
Reference (SYNTHETIC/L0, N=16): re-ID 100% shield-off -> 4.7% shield-on
(chance 6.25%, below chance), throughput 97.6%, energy ratio 1.000000. 35 tests
+ doctest pass; clippy -D warnings clean; builds for wasm32.
Docs: new docs/research/privacy-shield/08-optimization.md; updated bundle
README/03/05/07 and ADR-288 with the derived operating point.
Co-Authored-By: claude-flow <ruv@ruv.net>
Claude-Session: https://claude.ai/code/session_01WEXNqzs7UsfNFBcP5yW21p