Use Ensemble Methods - AI Mitigation
AI MitigationUse an ensemble of models for inference to increase robustness to adversarial inputs. Some attacks may effectively evade one model or model family but be ineffective against others.
Overview
A source-backed snapshot of this defense.
Safeguard details
Where this defense applies and how the source classifies it.
- ATLAS ID
- AML.M0006
- Priority score
- 55
Covered techniques
Attacks this defense is designed to help with.
AML.T0010.001 - AI Software
Using multiple different models ensures minimal performance loss if security flaw is found in tool for one model or family.
AML.T0043.001 - Black-Box Optimization
Using an ensemble of models increases the difficulty of crafting effective adversarial data and improves overall robustness.
AML.T0043.002 - Black-Box Transfer
Using an ensemble of models increases the difficulty of crafting effective adversarial data and improves overall robustness.
AML.T0043 - Craft Adversarial Data
Using an ensemble of models increases the difficulty of crafting effective adversarial data and improves overall robustness.
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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.