Cover Image

Evaluating the Robustness of the "Ensemble Everything Everywhere" Defense

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Jie, Schlarmann, Christian, Nikolić, Kristina, Carlini, Nicholas, Croce, Francesco, Hein, Matthias, Tramèr, Florian
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adversarial ML Problems Are Getting Harder to Solve and to Evaluate
by: Rando, Javier, et al.
Published: (2025)

Evaluations of Machine Learning Privacy Defenses are Misleading
by: Aerni, Michael, et al.
Published: (2024)

Evading Black-box Classifiers Without Breaking Eggs
by: Debenedetti, Edoardo, et al.
Published: (2023)

Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining
by: Tramèr, Florian, et al.
Published: (2022)

The Jailbreak Tax: How Useful are Your Jailbreak Outputs?
by: Nikolić, Kristina, et al.
Published: (2025)

AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents
by: Debenedetti, Edoardo, et al.
Published: (2024)

AutoAdvExBench: Benchmarking autonomous exploitation of adversarial example defenses
by: Carlini, Nicholas, et al.
Published: (2025)

Privacy Backdoors: Stealing Data with Corrupted Pretrained Models
by: Feng, Shanglun, et al.
Published: (2024)

Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data
by: Zhang, Jie, et al.
Published: (2024)

Membership Inference Attacks on Sequence Models
by: Rossi, Lorenzo, et al.
Published: (2025)

Laundering AI Authority with Adversarial Examples
by: Zhang, Jie, et al.
Published: (2026)

Large-scale online deanonymization with LLMs
by: Lermen, Simon, et al.
Published: (2026)

Query-Based Adversarial Prompt Generation
by: Hayase, Jonathan, et al.
Published: (2024)

Blind Baselines Beat Membership Inference Attacks for Foundation Models
by: Das, Debeshee, et al.
Published: (2024)

JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models
by: Chao, Patrick, et al.
Published: (2024)

The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injections
by: Nasr, Milad, et al.
Published: (2025)

Perturb and Recover: Fine-tuning for Effective Backdoor Removal from CLIP
by: Singh, Naman Deep, et al.
Published: (2024)

Privacy Side Channels in Machine Learning Systems
by: Debenedetti, Edoardo, et al.
Published: (2023)

Cutting through buggy adversarial example defenses: fixing 1 line of code breaks Sabre
by: Carlini, Nicholas
Published: (2024)

Black-box Optimization of LLM Outputs by Asking for Directions
by: Zhang, Jie, et al.
Published: (2025)

Poisoning Web-Scale Training Datasets is Practical
by: Carlini, Nicholas, et al.
Published: (2023)

Adversarial Search Engine Optimization for Large Language Models
by: Nestaas, Fredrik, et al.
Published: (2024)

Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs
by: Rando, Javier, et al.
Published: (2024)

Adversarial Perturbations Cannot Reliably Protect Artists From Generative AI
by: Hönig, Robert, et al.
Published: (2024)

Remote Timing Attacks on Efficient Language Model Inference
by: Carlini, Nicholas, et al.
Published: (2024)

Universal Jailbreak Backdoors from Poisoned Human Feedback
by: Rando, Javier, et al.
Published: (2023)

Pruning Graphs by Adversarial Robustness Evaluation to Strengthen GNN Defenses
by: Wang, Yongyu
Published: (2025)

Evaluating the Robustness of a Production Malware Detection System to Transferable Adversarial Attacks
by: Nasr, Milad, et al.
Published: (2025)

CARE: Ensemble Adversarial Robustness Evaluation Against Adaptive Attackers for Security Applications
by: Zhang, Hangsheng, et al.
Published: (2024)

Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards
by: Huang, Yangsibo, et al.
Published: (2025)

Robustness Inspired Graph Backdoor Defense
by: Zhang, Zhiwei, et al.
Published: (2024)

Modal Aphasia: Can Unified Multimodal Models Describe Images From Memory?
by: Aerni, Michael, et al.
Published: (2025)

Shortcuts Everywhere and Nowhere: Exploring Multi-Trigger Backdoor Attacks
by: Li, Yige, et al.
Published: (2024)

IF-GUIDE: Influence Function-Guided Detoxification of LLMs
by: Coalson, Zachary, et al.
Published: (2025)

IDEA: Invariant Defense for Graph Adversarial Robustness
by: Tao, Shuchang, et al.
Published: (2023)

Certified Robustness to Clean-Label Poisoning Using Diffusion Denoising
by: Hong, Sanghyun, et al.
Published: (2024)

Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks
by: Andriushchenko, Maksym, et al.
Published: (2024)

Federated Bayesian Network Ensembles
by: van Daalen, Florian, et al.
Published: (2024)

Strategic Dishonesty Can Undermine AI Safety Evaluations of Frontier LLMs
by: Panfilov, Alexander, et al.
Published: (2025)

Certified Causal Defense with Generalizable Robustness
by: Qiao, Yiran, et al.
Published: (2024)