Erode AI Model Integrity
Description
Adversaries may degrade the target model's performance with adversarial data inputs to erode confidence in the system over time.
This can lead to the victim organization wasting time and money both attempting to fix the system and performing the tasks it was meant to automate by hand.
- ATLAS ID
- AML.T0031
- Maturity
- RealizedUsed by real adversaries against AI systems in the wild.
- Platforms
- Predictive AIGenerative AIAgentic AI
Mitigations
- AML.M0003Predictive AI Model Hardening
Hardened models are less susceptible to integrity attacks.
- AML.M0006Predictive AI Ensembles
Using multiple different models increases robustness to attack.
- AML.M0010Predictive AI Input Restoration
Preprocessing model inputs can prevent malicious data from going through the machine learning pipeline.
- AML.M0015Predictive AI Adversarial Input Detection
Incorporate adversarial input detection into the pipeline before inputs reach the model.