Evasion Attacks
AI Risk"Evasion attacks [145] target to cause significant shifts in model’s prediction via adding perturbations in the test samples to build adversarial examples. In specific, the perturbations can be implemented based on word changes, gradients, etc."
Overview
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MITRISK-Cui2024-02.10.06 - Evasion Attacks
"Evasion attacks [145] target to cause significant shifts in model’s prediction via adding perturbations in the test samples to build adversarial examples. In specific, the perturbations can be implemented based on word changes, gradients, etc."
MITRISK-IBM2025-65.09.03 - Evasion attack
"Evasion attacks attempt to make a model output incorrect results by slightly perturbing the input data that is sent to the trained model."
Mitigations
Defenses that may help with related attacks.
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Source evidence
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Included resource
Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems
Original source
MIT AI Risk Repository
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