FIG.04

Inversion & Privacy

Analysis of privacy leakage modalities where attacker queries reconstruct sensitive training data or infer membership status.

Threat Model Scope
Data Extraction
PII Leakage
DP Guarantees
Membership

Inference Attack

Determining if a specific record was included in the training dataset.

Attribute

Inference Attack

Inferring missing attributes of a record given partial knowledge.

Model

Inversion Attack

Reconstructing representative examples of a target class or specific record.

Prompt

Leakage (LLMs)

Extracting system prompts, verbatim training data, or PII via adversarial prompting.

RECONSTRUCTION PIPELINE

Attacker Queries

Targeted optimization over input space

TARGET

Target Model f(x)

Model Responses

Confidence scores / logits

CRITICAL LEAKAGE

Reconstructed Features

Sensitive Record ID: 8992
Name: REDACTED
Diagnosis: REDACTED
SSN: ***-**-****
Risk Controls
Control Status Efficacy
Differential Privacy (DP-SGD) ACTIVE High
PII Filtering Pipeline TESTING Med
Access Tiers (RBAC) ACTIVE High
Data Retention Limits ACTIVE Low
Query Auditing FAILING None
Measurement
ε (Epsilon)
2.45
MIA AUC
0.82
Recon. Sim.
94%

Data Lifecycle Privacy Gates

STAGE 1

Collection

  • Consent Logs
  • Source Validation
GATE: INGESTION
STAGE 2

Storage

  • Encryption At-Rest
  • Hard Deletion
GATE: RETRIEVAL
STAGE 3

Training

  • DP-SGD Active
  • Gradient Clipping
GATE: DEPLOYMENT
STAGE 4

Serving

  • Auth/RBAC
  • Query Auditing
VULNERABLE