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Differentially Private Score Release

director_ai.core.federated_privacy.score_release.DifferentialPrivacyScoreReleaser 

DifferentialPrivacyScoreReleaser(*, epsilon: float, sensitivity: float = 1.0, accountant: PrivacyAccountant | None = None, seed: int | None = None, allow_insecure_seed: bool = False)

Laplace mechanism wrapper for public or cross-tenant score release.

Internal guard decisions should continue to use raw scores. This class exists for dashboards, analytics exports, public benchmark summaries, or other disclosure surfaces where releasing the exact score could leak membership information about the underlying retrieval corpus.

director_ai.core.federated_privacy.score_release.PrivacyScoreRelease dataclass 

PrivacyScoreRelease(released_score: float, noise: float, epsilon_spent: float, sensitivity: float, mechanism: str, label: str, tenant_id: str = '', threshold: float | None = None, raw_score_included: bool = False)

Tenant-safe differentially private score release record.

Boundary

DifferentialPrivacyScoreReleaser adds calibrated Laplace noise to coherence scores before they are exposed outside the runtime trust boundary. It is for dashboards, analytics exports, cross-tenant aggregates, and public summaries where an exact score could leak membership information about the retrieval corpus.

It is not used for internal enforcement decisions. Halt and approval logic should continue to use raw scores inside the protected runtime.

from director_ai.core import DifferentialPrivacyScoreReleaser
from director_ai.core.federated_privacy import PrivacyAccountant

accountant = PrivacyAccountant(max_epsilon=5.0)
releaser = DifferentialPrivacyScoreReleaser(
    epsilon=0.25,
    sensitivity=1.0,
    accountant=accountant,
)

release = releaser.release_score(
    score.raw_score,
    label="public-dashboard",
    tenant_id="tenant-a",
    threshold=0.6,
)
publish(release.to_dict())

The release payload omits the raw score and carries mechanism, epsilon, sensitivity, and budget metadata. Use PrivacyAccountant to cap cumulative privacy loss across score disclosures.