SoK: Analyzing Adversarial Examples: A Framework to Study Adversary Knowledge

arXiv:2402.14937v1 Announce Type: cross
Abstract: 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 there is a lack of study and formalization of adversary knowledge when mounting attacks. This has yielded a complex space of attack research with hard-to-compare threat models and attacks. We focus on the image classification domain and provide a theoretical framework to study adversary knowledge inspired …

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