Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates
Fuente:
arXiv
Saved in:
| Main Authors: | Angioni, Daniele, Demetrio, Luca, Pintor, Maura, Oneto, Luca, Anguita, Davide, Biggio, Battista, Roli, Fabio |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches
by: Pintor, Maura, et al.
Published: (2022)
by: Pintor, Maura, et al.
Published: (2022)
Evaluating the Evaluators: Trust in Adversarial Robustness Tests
by: Cinà, Antonio Emanuele, et al.
Published: (2025)
by: Cinà, Antonio Emanuele, et al.
Published: (2025)
Robust Synthetic Data-Driven Detection of Living-Off-the-Land Reverse Shells
by: Trizna, Dmitrijs, et al.
Published: (2024)
by: Trizna, Dmitrijs, et al.
Published: (2024)
Regression-aware Continual Learning for Android Malware Detection
by: Ghiani, Daniele, et al.
Published: (2025)
by: Ghiani, Daniele, et al.
Published: (2025)
Nebula: Self-Attention for Dynamic Malware Analysis
by: Trizna, Dmitrijs, et al.
Published: (2023)
by: Trizna, Dmitrijs, et al.
Published: (2023)
Adversarial Pruning: A Survey and Benchmark of Pruning Methods for Adversarial Robustness
by: Piras, Giorgio, et al.
Published: (2024)
by: Piras, Giorgio, et al.
Published: (2024)
secml-malware: Pentesting Windows Malware Classifiers with Adversarial EXEmples in Python
by: Demetrio, Luca, et al.
Published: (2021)
by: Demetrio, Luca, et al.
Published: (2021)
Label-efficient Training Updates for Malware Detection over Time
by: Minnei, Luca, et al.
Published: (2026)
by: Minnei, Luca, et al.
Published: (2026)
Demystifying the Role of Rule-based Detection in AI Systems for Windows Malware Detection
by: Ponte, Andrea, et al.
Published: (2025)
by: Ponte, Andrea, et al.
Published: (2025)
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
by: Cinà, Antonio Emanuele, et al.
Published: (2024)
by: Cinà, Antonio Emanuele, et al.
Published: (2024)
ModSec-AdvLearn: Countering Adversarial SQL Injections with Robust Machine Learning
by: Floris, Giuseppe, et al.
Published: (2023)
by: Floris, Giuseppe, et al.
Published: (2023)
Updating Windows Malware Detectors: Balancing Robustness and Regression against Adversarial EXEmples
by: Kozak, Matous, et al.
Published: (2024)
by: Kozak, Matous, et al.
Published: (2024)
Prototype-Guided Robust Learning against Backdoor Attacks
by: Guo, Wei, et al.
Published: (2025)
by: Guo, Wei, et al.
Published: (2025)
Evaluating Line-level Localization Ability of Learning-based Code Vulnerability Detection Models
by: Pintore, Marco, et al.
Published: (2025)
by: Pintore, Marco, et al.
Published: (2025)
SLIFER: Investigating Performance and Robustness of Malware Detection Pipelines
by: Ponte, Andrea, et al.
Published: (2024)
by: Ponte, Andrea, et al.
Published: (2024)
Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing
by: Gibert, Daniel, et al.
Published: (2024)
by: Gibert, Daniel, et al.
Published: (2024)
Silent Until Sparse: Backdoor Attacks on Semi-Structured Sparsity
by: Guo, Wei, et al.
Published: (2025)
by: Guo, Wei, et al.
Published: (2025)
Empirical Quantification of Spurious Correlations in Malware Detection
by: Perasso, Bianca, et al.
Published: (2025)
by: Perasso, Bianca, et al.
Published: (2025)
BlackCATT: Black-box Collusion Aware Traitor Tracing in Federated Learning
by: Rodríguez-Lois, Elena, et al.
Published: (2026)
by: Rodríguez-Lois, Elena, et al.
Published: (2026)
$σ$-zero: Gradient-based Optimization of $\ell_0$-norm Adversarial Examples
by: Cinà, Antonio Emanuele, et al.
Published: (2024)
by: Cinà, Antonio Emanuele, et al.
Published: (2024)
Machine Learning Security against Data Poisoning: Are We There Yet?
by: Cinà, Antonio Emanuele, et al.
Published: (2022)
by: Cinà, Antonio Emanuele, et al.
Published: (2022)
Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions
by: Cinà, Antonio Emanuele, et al.
Published: (2021)
by: Cinà, Antonio Emanuele, et al.
Published: (2021)
Energy-Latency Attacks via Sponge Poisoning
by: Cinà, Antonio Emanuele, et al.
Published: (2022)
by: Cinà, Antonio Emanuele, et al.
Published: (2022)
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis
by: Gupta, Srishti, et al.
Published: (2024)
by: Gupta, Srishti, et al.
Published: (2024)
Sonic: Fast and Transferable Data Poisoning on Clustering Algorithms
by: Villani, Francesco, et al.
Published: (2024)
by: Villani, Francesco, et al.
Published: (2024)
Buffer-free Class-Incremental Learning with Out-of-Distribution Detection
by: Gupta, Srishti, et al.
Published: (2025)
by: Gupta, Srishti, et al.
Published: (2025)
Trust Under Siege: Label Spoofing Attacks against Machine Learning for Android Malware Detection
by: Lan, Tianwei, et al.
Published: (2025)
by: Lan, Tianwei, et al.
Published: (2025)
Latent-space Attacks for Refusal Evasion in Language Models
by: Piras, Giorgio, et al.
Published: (2026)
by: Piras, Giorgio, et al.
Published: (2026)
Security of Deep Reinforcement Learning for Autonomous Driving: A Survey
by: Demontis, Ambra, et al.
Published: (2022)
by: Demontis, Ambra, et al.
Published: (2022)
On the Robustness of Adversarial Training Against Uncertainty Attacks
by: Ledda, Emanuele, et al.
Published: (2024)
by: Ledda, Emanuele, et al.
Published: (2024)
Plinius: Secure and Persistent Machine Learning Model Training
by: Yuhala, Peterson, et al.
Published: (2021)
by: Yuhala, Peterson, et al.
Published: (2021)
Moshi Moshi? A Model Selection Hijacking Adversarial Attack
by: Petrucci, Riccardo, et al.
Published: (2025)
by: Petrucci, Riccardo, et al.
Published: (2025)
On the Robustness of Bayesian Neural Networks to Adversarial Attacks
by: Bortolussi, Luca, et al.
Published: (2022)
by: Bortolussi, Luca, et al.
Published: (2022)
SOM Directions are Better than One: Multi-Directional Refusal Suppression in Language Models
by: Piras, Giorgio, et al.
Published: (2025)
by: Piras, Giorgio, et al.
Published: (2025)
Vision Transformer with Adversarial Indicator Token against Adversarial Attacks in Radio Signal Classifications
by: Zhang, Lu, et al.
Published: (2025)
by: Zhang, Lu, et al.
Published: (2025)
Towards Sustainable SecureML: Quantifying Carbon Footprint of Adversarial Machine Learning
by: Hasan, Syed Mhamudul, et al.
Published: (2024)
by: Hasan, Syed Mhamudul, et al.
Published: (2024)
Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation
by: Yang, Kun, et al.
Published: (2025)
by: Yang, Kun, et al.
Published: (2025)
Covert Attacks on Machine Learning Training in Passively Secure MPC
by: Jagielski, Matthew, et al.
Published: (2025)
by: Jagielski, Matthew, et al.
Published: (2025)
One Detector Fits All: Robust and Adaptive Detection of Malicious Packages from PyPI to Enterprises
by: Montaruli, Biagio, et al.
Published: (2025)
by: Montaruli, Biagio, et al.
Published: (2025)
Vulnerability-Aware Robust Multimodal Adversarial Training
by: Zhang, Junrui, et al.
Published: (2025)
by: Zhang, Junrui, et al.
Published: (2025)
Similar Items
-
ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches
by: Pintor, Maura, et al.
Published: (2022) -
Evaluating the Evaluators: Trust in Adversarial Robustness Tests
by: Cinà, Antonio Emanuele, et al.
Published: (2025) -
Robust Synthetic Data-Driven Detection of Living-Off-the-Land Reverse Shells
by: Trizna, Dmitrijs, et al.
Published: (2024) -
Regression-aware Continual Learning for Android Malware Detection
by: Ghiani, Daniele, et al.
Published: (2025) -
Nebula: Self-Attention for Dynamic Malware Analysis
by: Trizna, Dmitrijs, et al.
Published: (2023)