Infer Training Data Membership - AI Security Technique
AI Security TechniqueAdversaries may infer the membership of a data sample or global characteristics of the data in its training set, which raises privacy concerns. Some strategies make use of a shadow model that could be obtained via Train Proxy via Replication, others use statistics of model prediction scores. This can cause the victim model to leak private information, such as PII of those in the traini...
Overview
A source-backed snapshot of this AI security technique.
Adversaries may infer the membership of a data sample or global characteristics of the data in its training set, which raises privacy concerns. Some strategies make use of a shadow model that could be obtained via Train Proxy via Replication, others use statistics of model prediction scores.
This can cause the victim model to leak private information, such as PII of those in the training set or other forms of protected IP.
Technique details
Identifiers, maturity, and source taxonomy for this technique.
- ATLAS ID
- AML.T0024.000
- Maturity
- feasible
- Priority score
- 19
Attack flow
How to read the public records connected to this technique.
Impact
Why this technique may deserve attention in the current dataset.
- Evidence levelfeasible
- Mapped defenses3 ATLAS mitigation records
- Public examples0 linked case study records
- Research risks0 related MIT AI Risk records above the confidence threshold
- Vulnerabilities0 linked CVE records
Mitigations
Defenses that may help against this attack.
AML.M0024 - AI Telemetry Logging
Telemetry logging can help identify if sensitive data has been exfiltrated.
AML.M0002 - Passive AI Output Obfuscation
Suggested approaches:
- Restrict the number of results shown
- Limit specificity of output class ontology
- Use randomized smoothing techniques
- Reduce the precision of numerical outputs
AML.M0004 - Restrict Number of AI Model Queries
Limit the volume of API queries in a given period of time to regulate the amount and fidelity of potentially sensitive information an attacker can learn.
Case studies
Examples from public reports and exercises.
Source evidence
Original public records and references for this page.
Original source
Original source links
Open the public records and source datasets used for this page.
