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Found 8 papers, 2 papers with code
PRP: Propagating Universal Perturbations to Attack Large Language Model Guard-Rails
More recent LLMs often incorporate an additional layer of defense, a Guard Model, which is a second LLM that is designed to check and moderate the output response of the primary LLM.
Do Large Code Models Understand Programming Concepts? A Black-box Approach
Large Language Models' success on text generation has also made them better at code generation and coding tasks.
Theoretically Principled Trade-off for Stateful Defenses against Query-Based Black-Box Attacks
This work aims to address this gap by offering a theoretical characterization of the trade-off between detection and false positive rates for stateful defenses.
Stateful Defenses for Machine Learning Models Are Not Yet Secure Against Black-box Attacks
Such stateful defenses aim to defend against black-box attacks by tracking the query history and detecting and rejecting queries that are "similar" and thus preventing black-box attacks from finding useful gradients and making progress towards finding adversarial attacks within a reasonable query budget.
SkillFence: A Systems Approach to Practically Mitigating Voice-Based Confusion Attacks
Our key insight is that we can interpret a user's intentions by analyzing their activity on counterpart systems of the web and smartphones.
Re-purposing Perceptual Hashing based Client Side Scanning for Physical Surveillance
Content scanning systems employ perceptual hashing algorithms to scan user content for illegal material, such as child pornography or terrorist recruitment flyers.
D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles
D4 uses an ensemble of models over disjoint subsets of the frequency spectrum to significantly improve adversarial robustness.
Invisible Perturbations: Physical Adversarial Examples Exploiting the Rolling Shutter Effect
By contrast, we contribute a procedure to generate, for the first time, physical adversarial examples that are invisible to human eyes.
