Prototype-Guided Robust Learning against Backdoor Attacks
Fuente:
arXiv
Saved in:
| Main Authors: | Guo, Wei, Pintor, Maura, Demontis, Ambra, Biggio, Battista |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Silent Until Sparse: Backdoor Attacks on Semi-Structured Sparsity
by: Guo, Wei, et al.
Published: (2025)
by: Guo, Wei, et al.
Published: (2025)
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)
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)
Evaluating the Evaluators: Trust in Adversarial Robustness Tests
by: Cinà, Antonio Emanuele, et al.
Published: (2025)
by: Cinà, Antonio Emanuele, et al.
Published: (2025)
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)
AttackBench: Evaluating Gradient-based Attacks for 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)
Energy-Latency Attacks via Sponge Poisoning
by: Cinà, Antonio Emanuele, et al.
Published: (2022)
by: Cinà, Antonio Emanuele, et al.
Published: (2022)
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)
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)
Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates
by: Angioni, Daniele, et al.
Published: (2024)
by: Angioni, Daniele, 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)
Regression-aware Continual Learning for Android Malware Detection
by: Ghiani, Daniele, et al.
Published: (2025)
by: Ghiani, Daniele, et al.
Published: (2025)
$σ$-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)
Label-efficient Training Updates for Malware Detection over Time
by: Minnei, Luca, et al.
Published: (2026)
by: Minnei, Luca, et al.
Published: (2026)
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)
Backdoor Attacks against Hybrid Classical-Quantum Neural Networks
by: Guo, Ji, et al.
Published: (2024)
by: Guo, Ji, et al.
Published: (2024)
Poisoning ML attack and defenses
by: Battista, Biggio, et al.
Published: (2025)
by: Battista, Biggio, et al.
Published: (2025)
Stealthy Targeted Backdoor Attacks against Image Captioning
by: Fan, Wenshu, et al.
Published: (2024)
by: Fan, Wenshu, et al.
Published: (2024)
UltraClean: A Simple Framework to Train Robust Neural Networks against Backdoor Attacks
by: Zhao, Bingyin, et al.
Published: (2023)
by: Zhao, Bingyin, et al.
Published: (2023)
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)
Dullahan: Stealthy Backdoor Attack against Without-Label-Sharing Split Learning
by: Pu, Yuwen, et al.
Published: (2024)
by: Pu, Yuwen, et al.
Published: (2024)
Adversarial Inception Backdoor Attacks against Reinforcement Learning
by: Rathbun, Ethan, et al.
Published: (2024)
by: Rathbun, Ethan, et al.
Published: (2024)
Combinational Backdoor Attack against Customized Text-to-Image Models
by: Jiang, Wenbo, et al.
Published: (2024)
by: Jiang, Wenbo, et al.
Published: (2024)
DETOUR: A Practical Backdoor Attack against Object Detection
by: Liu, Dazhuang, et al.
Published: (2026)
by: Liu, Dazhuang, et al.
Published: (2026)
SAB:A Stealing and Robust Backdoor Attack based on Steganographic Algorithm against Federated Learning
by: Xu, Weida, et al.
Published: (2024)
by: Xu, Weida, et al.
Published: (2024)
Lurking in the shadows: Unveiling Stealthy Backdoor Attacks against Personalized Federated Learning
by: Lyu, Xiaoting, et al.
Published: (2024)
by: Lyu, Xiaoting, et al.
Published: (2024)
TraceGuard: Process-Guided Firewall against Reasoning Backdoors in Large Language Models
by: Guo, Zhen, et al.
Published: (2026)
by: Guo, Zhen, et al.
Published: (2026)
Persistent Backdoor Attacks in Continual Learning
by: Guo, Zhen, et al.
Published: (2024)
by: Guo, Zhen, et al.
Published: (2024)
Nebula: Self-Attention for Dynamic Malware Analysis
by: Trizna, Dmitrijs, et al.
Published: (2023)
by: Trizna, Dmitrijs, et al.
Published: (2023)
Provable Robustness against Backdoor Attacks via the Primal-Dual Perspective on Differential Privacy
by: Saxena, Aman, et al.
Published: (2026)
by: Saxena, Aman, et al.
Published: (2026)
SLIFER: Investigating Performance and Robustness of Malware Detection Pipelines
by: Ponte, Andrea, et al.
Published: (2024)
by: Ponte, Andrea, et al.
Published: (2024)
Let's Focus: Focused Backdoor Attack against Federated Transfer Learning
by: Arazzi, Marco, et al.
Published: (2024)
by: Arazzi, Marco, et al.
Published: (2024)
Imperio: Language-Guided Backdoor Attacks for Arbitrary Model Control
by: Chow, Ka-Ho, et al.
Published: (2024)
by: Chow, Ka-Ho, et al.
Published: (2024)
Defending against Backdoor Attack on Deep Neural Networks
by: Cheng, Hao, et al.
Published: (2020)
by: Cheng, Hao, et al.
Published: (2020)
Invariant Aggregator for Defending against Federated Backdoor Attacks
by: Wang, Xiaoyang, et al.
Published: (2022)
by: Wang, Xiaoyang, et al.
Published: (2022)
Robust Knowledge Distillation in Federated Learning: Counteracting Backdoor Attacks
by: Alharbi, Ebtisaam, et al.
Published: (2025)
by: Alharbi, Ebtisaam, et al.
Published: (2025)
SNEAKDOOR: Stealthy Backdoor Attacks against Distribution Matching-based Dataset Condensation
by: Yang, He, et al.
Published: (2026)
by: Yang, He, et al.
Published: (2026)
Practical, Generalizable and Robust Backdoor Attacks on Text-to-Image Diffusion Models
by: Dai, Haoran, et al.
Published: (2025)
by: Dai, Haoran, et al.
Published: (2025)
A Universal Identity Backdoor Attack against Speaker Verification based on Siamese Network
by: Zhao, Haodong, et al.
Published: (2023)
by: Zhao, Haodong, et al.
Published: (2023)
Similar Items
-
Silent Until Sparse: Backdoor Attacks on Semi-Structured Sparsity
by: Guo, Wei, et al.
Published: (2025) -
ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches
by: Pintor, Maura, et al.
Published: (2022) -
Adversarial Pruning: A Survey and Benchmark of Pruning Methods for Adversarial Robustness
by: Piras, Giorgio, et al.
Published: (2024) -
Evaluating the Evaluators: Trust in Adversarial Robustness Tests
by: Cinà, Antonio Emanuele, et al.
Published: (2025) -
Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions
by: Cinà, Antonio Emanuele, et al.
Published: (2021)