Cover Image

On the Robustness of Adversarial Training Against Uncertainty Attacks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ledda, Emanuele, Scodeller, Giovanni, Angioni, Daniele, Piras, Giorgio, Cinà, Antonio Emanuele, Fumera, Giorgio, Biggio, Battista, Roli, Fabio
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adversarial Pruning: A Survey and Benchmark of Pruning Methods for Adversarial Robustness
by: Piras, Giorgio, et al.
Published: (2024)

Energy-Latency Attacks via Sponge Poisoning
by: Cinà, Antonio Emanuele, et al.
Published: (2022)

Evaluating the Evaluators: Trust in Adversarial Robustness Tests
by: Cinà, Antonio Emanuele, et al.
Published: (2025)

Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates
by: Angioni, Daniele, et al.
Published: (2024)

AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
by: Cinà, Antonio Emanuele, et al.
Published: (2024)

Regression-aware Continual Learning for Android Malware Detection
by: Ghiani, Daniele, et al.
Published: (2025)

SOM Directions are Better than One: Multi-Directional Refusal Suppression in Language Models
by: Piras, Giorgio, et al.
Published: (2025)

HO-FMN: Hyperparameter Optimization for Fast Minimum-Norm Attacks
by: Mura, Raffaele, et al.
Published: (2024)

ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches
by: Pintor, Maura, et al.
Published: (2022)

Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions
by: Cinà, Antonio Emanuele, et al.
Published: (2021)

Sonic: Fast and Transferable Data Poisoning on Clustering Algorithms
by: Villani, Francesco, et al.
Published: (2024)

Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis
by: Gupta, Srishti, et al.
Published: (2024)

Exploiting Edge Features for Transferable Adversarial Attacks in Distributed Machine Learning
by: Rossolini, Giulio, et al.
Published: (2025)

S2AP: Score-space Sharpness Minimization for Adversarial Pruning
by: Piras, Giorgio, et al.
Published: (2025)

Robust Synthetic Data-Driven Detection of Living-Off-the-Land Reverse Shells
by: Trizna, Dmitrijs, et al.
Published: (2024)

$σ$-zero: Gradient-based Optimization of $\ell_0$-norm Adversarial Examples
by: Cinà, Antonio Emanuele, et al.
Published: (2024)

SAGE-5GC: Security-Aware Guidelines for Evaluating Anomaly Detection in the 5G Core Network
by: Manca, Cristian, et al.
Published: (2026)

Label-efficient Training Updates for Malware Detection over Time
by: Minnei, Luca, et al.
Published: (2026)

Evaluating Line-level Localization Ability of Learning-based Code Vulnerability Detection Models
by: Pintore, Marco, et al.
Published: (2025)

Buffer-free Class-Incremental Learning with Out-of-Distribution Detection
by: Gupta, Srishti, et al.
Published: (2025)

Nebula: Self-Attention for Dynamic Malware Analysis
by: Trizna, Dmitrijs, et al.
Published: (2023)

Latent-space Attacks for Refusal Evasion in Language Models
by: Piras, Giorgio, et al.
Published: (2026)

Robust image classification with multi-modal large language models
by: Villani, Francesco, et al.
Published: (2024)

LatentBreak: Jailbreaking Large Language Models through Latent Space Feedback
by: Mura, Raffaele, et al.
Published: (2025)

Machine Learning Security against Data Poisoning: Are We There Yet?
by: Cinà, Antonio Emanuele, et al.
Published: (2022)

Out-of-Distribution Detection for Continual Learning: Design Principles and Benchmarking
by: Gupta, Srishti, et al.
Published: (2025)

ModSec-AdvLearn: Countering Adversarial SQL Injections with Robust Machine Learning
by: Floris, Giuseppe, et al.
Published: (2023)

A Neural Rejection System Against Universal Adversarial Perturbations in Radio Signal Classification
by: Zhang, Lu, et al.
Published: (2025)

Low-Rank Adversarial PGD Attack
by: Savostianova, Dayana, et al.
Published: (2024)

Dynamic Label Adversarial Training for Deep Learning Robustness Against Adversarial Attacks
by: Liu, Zhenyu, et al.
Published: (2024)

Security of Deep Reinforcement Learning for Autonomous Driving: A Survey
by: Demontis, Ambra, et al.
Published: (2022)

Vision Transformer with Adversarial Indicator Token against Adversarial Attacks in Radio Signal Classifications
by: Zhang, Lu, et al.
Published: (2025)

A New Formulation for Zeroth-Order Optimization of Adversarial EXEmples in Malware Detection
by: Rando, Marco, et al.
Published: (2024)

Membership and Dataset Inference Attacks on Large Audio Generative Models
by: Proboszcz, Jakub, et al.
Published: (2025)

How Neural Losses Shape VAE Latents
by: Strano, Giorgio, et al.
Published: (2026)

Inducing Causal Structure for Interpretable Neural Networks Applied to Glucose Prediction for T1DM Patients
by: Esponera, Ana, et al.
Published: (2025)

Adversarial Training for Defense Against Label Poisoning Attacks
by: Bal, Melis Ilayda, et al.
Published: (2025)

Robustness Against Adversarial Attacks via Learning Confined Adversarial Polytopes
by: Hamidi, Shayan Mohajer, et al.
Published: (2024)

Provable Robustness Against a Union of $\ell_0$ Adversarial Attacks
by: Hammoudeh, Zayd, et al.
Published: (2023)

Attention-based Adversarial Robust Distillation in Radio Signal Classifications for Low-Power IoT Devices
by: Zhang, Lu, et al.
Published: (2025)