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cs.LG2025
On the Trade-Off Between Transparency and Security in Adversarial Machine Learning
Lucas Fenaux, Christopher Srinivasa, Florian Kerschbaum
Transparency and security are both central to Responsible AI, but they may conflict in adversarial settings. We investigate the strategic effect of transparency for agents through…
cs.LG2024
SoK: Analyzing Adversarial Examples: A Framework to Study Adversary Knowledge
Lucas Fenaux, Florian Kerschbaum
Adversarial examples are malicious inputs to machine learning models that trigger a misclassification. This type of attack has been studied for close to a decade, and we find that…