Certified but Fooled! Breaking Certified Defences with Ghost Certificates
Quoc Viet Vo, Tashreque M. Haq, Paul Montague, Tamas Abraham, Ehsan Abbasnejad, Damith C. Ranasinghe

TL;DR
This paper reveals how adversaries can exploit probabilistic certification frameworks to generate imperceptible perturbations that spoof robustness guarantees, effectively bypassing state-of-the-art certified defenses like Densepure.
Contribution
It demonstrates the feasibility of crafting small, region-focused adversarial examples that deceive certified defenses, exposing vulnerabilities in current robustness certification methods.
Findings
Effective bypass of Densepure certification using ghost certificates
Imperceptible perturbations can generate false robustness guarantees
Extensive evaluations on ImageNet validate the attack method
Abstract
Certified defenses promise provable robustness guarantees. We study the malicious exploitation of probabilistic certification frameworks to better understand the limits of guarantee provisions. Now, the objective is to not only mislead a classifier, but also manipulate the certification process to generate a robustness guarantee for an adversarial input certificate spoofing. A recent study in ICLR demonstrated that crafting large perturbations can shift inputs far into regions capable of generating a certificate for an incorrect class. Our study investigates if perturbations needed to cause a misclassification and yet coax a certified model into issuing a deceptive, large robustness radius for a target class can still be made small and imperceptible. We explore the idea of region-focused adversarial examples to craft imperceptible perturbations, spoof certificates and achieve…
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Taxonomy
TopicsAdversarial Robustness in Machine Learning · Generative Adversarial Networks and Image Synthesis · Domain Adaptation and Few-Shot Learning
