On the Adversarial Robustness of Decision Trees and a Symmetry Defense

On the Adversarial Robustness of Decision Trees and a Symmetry Defense

Gradient-boosting decision tree classifiers (GBDTs) are susceptible to adversarial perturbation attacks that change inputs slightly to cause misclassification. GBDTs are customarily used on non-image datasets that lack inherent symmetries, which might be why data symmetry in the context of GBDT clas...

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Bibliographic Details
Main Author: Blerta Lindqvist
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Adversarial perturbation attacks
adversarial robustness
equivariance
gradient-boosting decision trees
invariance
symmetry defense
Online Access:https://ieeexplore.ieee.org/document/10843676/
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https://ieeexplore.ieee.org/document/10843676/

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