Copertina

AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Cinà, Antonio Emanuele, Rony, Jérôme, Pintor, Maura, Demetrio, Luca, Demontis, Ambra, Biggio, Battista, Ayed, Ismail Ben, Roli, Fabio
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Cryptography and Security Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

Prototype-Guided Robust Learning against Backdoor Attacks
di: Guo, Wei, et al.
Pubblicazione: (2025)

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

Silent Until Sparse: Backdoor Attacks on Semi-Structured Sparsity
di: Guo, Wei, et al.
Pubblicazione: (2025)

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

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

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

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

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

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

secml-malware: Pentesting Windows Malware Classifiers with Adversarial EXEmples in Python
di: Demetrio, Luca, et al.
Pubblicazione: (2021)

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

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

Demystifying the Role of Rule-based Detection in AI Systems for Windows Malware Detection
di: Ponte, Andrea, et al.
Pubblicazione: (2025)

SLIFER: Investigating Performance and Robustness of Malware Detection Pipelines
di: Ponte, Andrea, et al.
Pubblicazione: (2024)

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

BlackCATT: Black-box Collusion Aware Traitor Tracing in Federated Learning
di: Rodríguez-Lois, Elena, et al.
Pubblicazione: (2026)

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

Updating Windows Malware Detectors: Balancing Robustness and Regression against Adversarial EXEmples
di: Kozak, Matous, et al.
Pubblicazione: (2024)

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

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

Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing
di: Gibert, Daniel, et al.
Pubblicazione: (2024)

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

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

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

XAI-Based Detection of Adversarial Attacks on Deepfake Detectors
di: Pinhasov, Ben, et al.
Pubblicazione: (2024)

Effectiveness of Adversarial Benign and Malware Examples in Evasion and Poisoning Attacks
di: Kozák, Matouš, et al.
Pubblicazione: (2025)

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

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

Evasive Ransomware Attacks Using Low-level Behavioral Adversarial Examples
di: Hirano, Manabu, et al.
Pubblicazione: (2025)

Empirical Quantification of Spurious Correlations in Malware Detection
di: Perasso, Bianca, et al.
Pubblicazione: (2025)

BlackboxBench: A Comprehensive Benchmark of Black-box Adversarial Attacks
di: Zheng, Meixi, et al.
Pubblicazione: (2023)

The Gradient Puppeteer: Adversarial Domination in Gradient Leakage Attacks through Model Poisoning
di: Xiang, Kunlan, et al.
Pubblicazione: (2025)

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

Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization
di: Maljkovic, Igor, et al.
Pubblicazione: (2026)

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

Poisoning ML attack and defenses
di: Battista, Biggio, et al.
Pubblicazione: (2025)

On the Robustness of Adversarial Training Against Uncertainty Attacks
di: Ledda, Emanuele, et al.
Pubblicazione: (2024)

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

RoboJailBench: Benchmarking Adversarial Attacks and Defenses in Embodied Robotic Agents
di: Yeke, Doguhuan, et al.
Pubblicazione: (2026)