$σ$-zero: Gradient-based Optimization of $\ell_0$-norm Adversarial Examples
Fuente:
arXiv
Guardado en:
| Autores principales: | Cinà, Antonio Emanuele, Villani, Francesco, Pintor, Maura, Schönherr, Lea, Biggio, Battista, Pelillo, Marcello |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
por: Cinà, Antonio Emanuele, et al.
Publicado: (2024)
por: Cinà, Antonio Emanuele, et al.
Publicado: (2024)
Energy-Latency Attacks via Sponge Poisoning
por: Cinà, Antonio Emanuele, et al.
Publicado: (2022)
por: Cinà, Antonio Emanuele, et al.
Publicado: (2022)
Evaluating the Evaluators: Trust in Adversarial Robustness Tests
por: Cinà, Antonio Emanuele, et al.
Publicado: (2025)
por: Cinà, Antonio Emanuele, et al.
Publicado: (2025)
Machine Learning Security against Data Poisoning: Are We There Yet?
por: Cinà, Antonio Emanuele, et al.
Publicado: (2022)
por: Cinà, Antonio Emanuele, et al.
Publicado: (2022)
Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions
por: Cinà, Antonio Emanuele, et al.
Publicado: (2021)
por: Cinà, Antonio Emanuele, et al.
Publicado: (2021)
Prototype-Guided Robust Learning against Backdoor Attacks
por: Guo, Wei, et al.
Publicado: (2025)
por: Guo, Wei, et al.
Publicado: (2025)
Silent Until Sparse: Backdoor Attacks on Semi-Structured Sparsity
por: Guo, Wei, et al.
Publicado: (2025)
por: Guo, Wei, et al.
Publicado: (2025)
Evaluating Line-level Localization Ability of Learning-based Code Vulnerability Detection Models
por: Pintore, Marco, et al.
Publicado: (2025)
por: Pintore, Marco, et al.
Publicado: (2025)
Sonic: Fast and Transferable Data Poisoning on Clustering Algorithms
por: Villani, Francesco, et al.
Publicado: (2024)
por: Villani, Francesco, et al.
Publicado: (2024)
Adversarial Pruning: A Survey and Benchmark of Pruning Methods for Adversarial Robustness
por: Piras, Giorgio, et al.
Publicado: (2024)
por: Piras, Giorgio, et al.
Publicado: (2024)
Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates
por: Angioni, Daniele, et al.
Publicado: (2024)
por: Angioni, Daniele, et al.
Publicado: (2024)
BlackCATT: Black-box Collusion Aware Traitor Tracing in Federated Learning
por: Rodríguez-Lois, Elena, et al.
Publicado: (2026)
por: Rodríguez-Lois, Elena, et al.
Publicado: (2026)
secml-malware: Pentesting Windows Malware Classifiers with Adversarial EXEmples in Python
por: Demetrio, Luca, et al.
Publicado: (2021)
por: Demetrio, Luca, et al.
Publicado: (2021)
Conning the Crypto Conman: End-to-End Analysis of Cryptocurrency-based Technical Support Scams
por: Acharya, Bhupendra, et al.
Publicado: (2024)
por: Acharya, Bhupendra, et al.
Publicado: (2024)
ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches
por: Pintor, Maura, et al.
Publicado: (2022)
por: Pintor, Maura, et al.
Publicado: (2022)
Label-efficient Training Updates for Malware Detection over Time
por: Minnei, Luca, et al.
Publicado: (2026)
por: Minnei, Luca, et al.
Publicado: (2026)
Regression-aware Continual Learning for Android Malware Detection
por: Ghiani, Daniele, et al.
Publicado: (2025)
por: Ghiani, Daniele, et al.
Publicado: (2025)
Pirates of Charity: Exploring Donation-based Abuses in Social Media Platforms
por: Acharya, Bhupendra, et al.
Publicado: (2024)
por: Acharya, Bhupendra, et al.
Publicado: (2024)
Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing
por: Gibert, Daniel, et al.
Publicado: (2024)
por: Gibert, Daniel, et al.
Publicado: (2024)
Robust image classification with multi-modal large language models
por: Villani, Francesco, et al.
Publicado: (2024)
por: Villani, Francesco, et al.
Publicado: (2024)
Rag and Roll: An End-to-End Evaluation of Indirect Prompt Manipulations in LLM-based Application Frameworks
por: De Stefano, Gianluca, et al.
Publicado: (2024)
por: De Stefano, Gianluca, et al.
Publicado: (2024)
Nebula: Self-Attention for Dynamic Malware Analysis
por: Trizna, Dmitrijs, et al.
Publicado: (2023)
por: Trizna, Dmitrijs, et al.
Publicado: (2023)
Robust Synthetic Data-Driven Detection of Living-Off-the-Land Reverse Shells
por: Trizna, Dmitrijs, et al.
Publicado: (2024)
por: Trizna, Dmitrijs, et al.
Publicado: (2024)
Generalization Properties of Adversarial Training for $\ell_0$-Bounded Adversarial Attacks
por: Delgosha, Payam, et al.
Publicado: (2024)
por: Delgosha, Payam, et al.
Publicado: (2024)
Demystifying the Role of Rule-based Detection in AI Systems for Windows Malware Detection
por: Ponte, Andrea, et al.
Publicado: (2025)
por: Ponte, Andrea, et al.
Publicado: (2025)
Prompt Obfuscation for Large Language Models
por: Pape, David, et al.
Publicado: (2024)
por: Pape, David, et al.
Publicado: (2024)
Whispers in the Machine: Confidentiality in Agentic Systems
por: Evertz, Jonathan, et al.
Publicado: (2024)
por: Evertz, Jonathan, et al.
Publicado: (2024)
Constraint-based Adversarial Example Synthesis
por: Yu, Fang, et al.
Publicado: (2024)
por: Yu, Fang, et al.
Publicado: (2024)
ModSec-AdvLearn: Countering Adversarial SQL Injections with Robust Machine Learning
por: Floris, Giuseppe, et al.
Publicado: (2023)
por: Floris, Giuseppe, et al.
Publicado: (2023)
IrisFP: Adversarial-Example-based Model Fingerprinting with Enhanced Uniqueness and Robustness
por: Geng, Ziye, et al.
Publicado: (2026)
por: Geng, Ziye, et al.
Publicado: (2026)
Detecting Adversarial Examples
por: Mumcu, Furkan, et al.
Publicado: (2024)
por: Mumcu, Furkan, et al.
Publicado: (2024)
Trust Me, I Know This Function: Hijacking LLM Static Analysis using Bias
por: Bernstein, Shir, et al.
Publicado: (2025)
por: Bernstein, Shir, et al.
Publicado: (2025)
SLIFER: Investigating Performance and Robustness of Malware Detection Pipelines
por: Ponte, Andrea, et al.
Publicado: (2024)
por: Ponte, Andrea, et al.
Publicado: (2024)
Effectiveness of Adversarial Benign and Malware Examples in Evasion and Poisoning Attacks
por: Kozák, Matouš, et al.
Publicado: (2025)
por: Kozák, Matouš, et al.
Publicado: (2025)
NeuroTrace: Inference Provenance-Based Detection of Adversarial Examples
por: Hmida, Firas Ben, et al.
Publicado: (2026)
por: Hmida, Firas Ben, et al.
Publicado: (2026)
Prediction Inconsistency Helps Achieve Generalizable Detection of Adversarial Examples
por: Han, Sicong, et al.
Publicado: (2025)
por: Han, Sicong, et al.
Publicado: (2025)
Transferability Ranking of Adversarial Examples
por: Levy, Mosh, et al.
Publicado: (2022)
por: Levy, Mosh, et al.
Publicado: (2022)
Evasive Ransomware Attacks Using Low-level Behavioral Adversarial Examples
por: Hirano, Manabu, et al.
Publicado: (2025)
por: Hirano, Manabu, et al.
Publicado: (2025)
Adversarial Example Based Fingerprinting for Robust Copyright Protection in Split Learning
por: Lin, Zhangting, et al.
Publicado: (2025)
por: Lin, Zhangting, et al.
Publicado: (2025)
Obfuscating IoT Device Scanning Activity via Adversarial Example Generation
por: Li, Haocong, et al.
Publicado: (2024)
por: Li, Haocong, et al.
Publicado: (2024)
Ejemplares similares
-
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
por: Cinà, Antonio Emanuele, et al.
Publicado: (2024) -
Energy-Latency Attacks via Sponge Poisoning
por: Cinà, Antonio Emanuele, et al.
Publicado: (2022) -
Evaluating the Evaluators: Trust in Adversarial Robustness Tests
por: Cinà, Antonio Emanuele, et al.
Publicado: (2025) -
Machine Learning Security against Data Poisoning: Are We There Yet?
por: Cinà, Antonio Emanuele, et al.
Publicado: (2022) -
Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions
por: Cinà, Antonio Emanuele, et al.
Publicado: (2021)