Assessing the Impact of Packing on Machine Learning-Based Malware Detection and Classification Systems
Fuente:
arXiv
Guardado en:
| Autores principales: | Gibert, Daniel, Totosis, Nikolaos, Patsakis, Constantinos, Zizzo, Giulio, Le, Quan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Towards a Practical Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via Randomized Smoothing
por: Gibert, Daniel, et al.
Publicado: (2023)
por: Gibert, Daniel, et al.
Publicado: (2023)
A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing
por: Gibert, Daniel, et al.
Publicado: (2024)
por: Gibert, Daniel, 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)
Machine Learning for Windows Malware Detection and Classification: Methods, Challenges and Ongoing Research
por: Gibert, Daniel
Publicado: (2024)
por: Gibert, Daniel
Publicado: (2024)
Coding Malware in Fancy Programming Languages for Fun and Profit
por: Apostolopoulos, Theodoros, et al.
Publicado: (2025)
por: Apostolopoulos, Theodoros, et al.
Publicado: (2025)
Assessing LLMs in Malicious Code Deobfuscation of Real-world Malware Campaigns
por: Patsakis, Constantinos, et al.
Publicado: (2024)
por: Patsakis, Constantinos, et al.
Publicado: (2024)
The Malware as a Service ecosystem
por: Patsakis, Constantinos, et al.
Publicado: (2024)
por: Patsakis, Constantinos, et al.
Publicado: (2024)
Fusing Feature Engineering and Deep Learning: A Case Study for Malware Classification
por: Gibert, Daniel, et al.
Publicado: (2022)
por: Gibert, Daniel, et al.
Publicado: (2022)
Blue Teaming Function-Calling Agents
por: Dolcetti, Greta, et al.
Publicado: (2026)
por: Dolcetti, Greta, et al.
Publicado: (2026)
Just in Plain Sight: Unveiling CSAM Distribution Campaigns on the Clear Web
por: Lykousas, Nikolaos, et al.
Publicado: (2025)
por: Lykousas, Nikolaos, et al.
Publicado: (2025)
Machine Learning Transferability for Malware Detection
por: Vieira, César, et al.
Publicado: (2026)
por: Vieira, César, et al.
Publicado: (2026)
System Calls for Malware Detection and Classification: Methodologies and Applications
por: Gond, Bishwajit Prasad, et al.
Publicado: (2025)
por: Gond, Bishwajit Prasad, et al.
Publicado: (2025)
A Unified Evaluation of Learning-Based Similarity Techniques for Malware Detection
por: Prasad, Udbhav, et al.
Publicado: (2026)
por: Prasad, Udbhav, et al.
Publicado: (2026)
Combating Concept Drift with Explanatory Detection and Adaptation for Android Malware Classification
por: He, Yiling, et al.
Publicado: (2024)
por: He, Yiling, et al.
Publicado: (2024)
Towards Assuring EU AI Act Compliance and Adversarial Robustness of LLMs
por: Momcilovic, Tomas Bueno, et al.
Publicado: (2024)
por: Momcilovic, Tomas Bueno, et al.
Publicado: (2024)
A Transformer-Based Framework for Payload Malware Detection and Classification
por: Stein, Kyle, et al.
Publicado: (2024)
por: Stein, Kyle, et al.
Publicado: (2024)
QRS: A Rule-Synthesizing Neuro-Symbolic Triad for Autonomous Vulnerability Discovery
por: Tsigkourakos, George, et al.
Publicado: (2026)
por: Tsigkourakos, George, et al.
Publicado: (2026)
Obfuscated Memory Malware Detection
por: P, Sharmila S, et al.
Publicado: (2024)
por: P, Sharmila S, 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)
Model X-Ray: Detection of Hidden Malware in AI Model Weights using Few Shot Learning
por: Gilkarov, Daniel, et al.
Publicado: (2024)
por: Gilkarov, Daniel, et al.
Publicado: (2024)
On the Reliability and Stability of Selective Methods in Malware Classification Tasks
por: Herzog, Alexander, et al.
Publicado: (2025)
por: Herzog, Alexander, et al.
Publicado: (2025)
Do You Trust Your Model? Emerging Malware Threats in the Deep Learning Ecosystem
por: Hitaj, Dorjan, et al.
Publicado: (2024)
por: Hitaj, Dorjan, et al.
Publicado: (2024)
Malware Detection Through Memory Analysis
por: Nassar, Sarah
Publicado: (2026)
por: Nassar, Sarah
Publicado: (2026)
MalCL: Leveraging GAN-Based Generative Replay to Combat Catastrophic Forgetting in Malware Classification
por: Park, Jimin, et al.
Publicado: (2025)
por: Park, Jimin, et al.
Publicado: (2025)
Android Malware Detection: A Machine Leaning Approach
por: Abdulla, Hasan
Publicado: (2025)
por: Abdulla, Hasan
Publicado: (2025)
Leveraging LSTM and GAN for Modern Malware Detection
por: Gupta, Ishita, et al.
Publicado: (2024)
por: Gupta, Ishita, et al.
Publicado: (2024)
Empirical Quantification of Spurious Correlations in Malware Detection
por: Perasso, Bianca, et al.
Publicado: (2025)
por: Perasso, Bianca, et al.
Publicado: (2025)
ByteShield: Adversarially Robust End-to-End Malware Detection through Byte Masking
por: Gibert, Daniel, et al.
Publicado: (2025)
por: Gibert, Daniel, et al.
Publicado: (2025)
LAMD: Context-driven Android Malware Detection and Classification with LLMs
por: Qian, Xingzhi, et al.
Publicado: (2025)
por: Qian, Xingzhi, et al.
Publicado: (2025)
The Power of MEME: Adversarial Malware Creation with Model-Based Reinforcement Learning
por: Rigaki, Maria, et al.
Publicado: (2023)
por: Rigaki, Maria, et al.
Publicado: (2023)
Explainable Malware Detection with Tailored Logic Explained Networks
por: Anthony, Peter, et al.
Publicado: (2024)
por: Anthony, Peter, et al.
Publicado: (2024)
SLIFER: Investigating Performance and Robustness of Malware Detection Pipelines
por: Ponte, Andrea, et al.
Publicado: (2024)
por: Ponte, Andrea, et al.
Publicado: (2024)
Developing Assurance Cases for Adversarial Robustness and Regulatory Compliance in LLMs
por: Momcilovic, Tomas Bueno, et al.
Publicado: (2024)
por: Momcilovic, Tomas Bueno, et al.
Publicado: (2024)
Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models
por: Belkhiter, Yannis, et al.
Publicado: (2026)
por: Belkhiter, Yannis, et al.
Publicado: (2026)
Learning Temporal Invariance in Android Malware Detectors
por: Zheng, Xinran, et al.
Publicado: (2025)
por: Zheng, Xinran, et al.
Publicado: (2025)
Malware analysis assisted by AI with R2AI
por: Apvrille, Axelle, et al.
Publicado: (2025)
por: Apvrille, Axelle, et al.
Publicado: (2025)
Use of Multi-CNNs for Section Analysis in Static Malware Detection
por: Quertier, Tony, et al.
Publicado: (2024)
por: Quertier, Tony, et al.
Publicado: (2024)
AI-Powered Algorithms for the Prevention and Detection of Computer Malware Infections
por: Keshava, Rakesh, et al.
Publicado: (2026)
por: Keshava, Rakesh, et al.
Publicado: (2026)
Automated Malware Family Classification using Weighted Hierarchical Ensembles of Large Language Models
por: Bai, Samita, et al.
Publicado: (2026)
por: Bai, Samita, et al.
Publicado: (2026)
Evaluating Ensemble and Deep Learning Models for Static Malware Detection with Dimensionality Reduction Using the EMBER Dataset
por: Abedin, Md Min-Ha-Zul, et al.
Publicado: (2025)
por: Abedin, Md Min-Ha-Zul, et al.
Publicado: (2025)
Ejemplares similares
-
Towards a Practical Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via Randomized Smoothing
por: Gibert, Daniel, et al.
Publicado: (2023) -
A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing
por: Gibert, Daniel, et al.
Publicado: (2024) -
Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing
por: Gibert, Daniel, et al.
Publicado: (2024) -
Machine Learning for Windows Malware Detection and Classification: Methods, Challenges and Ongoing Research
por: Gibert, Daniel
Publicado: (2024) -
Coding Malware in Fancy Programming Languages for Fun and Profit
por: Apostolopoulos, Theodoros, et al.
Publicado: (2025)