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Burning the Adversarial Bridges: Robust Windows Malware Detection
  Against Binary-level Mutations

Burning the Adversarial Bridges: Robust Windows Malware Detection Against Binary-level Mutations

5 October 2023
Ahmed A. Abusnaina
Yizhen Wang
Sunpreet S. Arora
Ke Wang
Mihai Christodorescu
David A. Mohaisen
    AAML
ArXiv (abs)PDFHTML

Papers citing "Burning the Adversarial Bridges: Robust Windows Malware Detection Against Binary-level Mutations"

3 / 3 papers shown
Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection
Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection
Ahmed Sabbah
Radi Jarrar
Samer Zein
David Mohaisen
98
1
0
30 Jul 2025
Large Language Model (LLM) for Software Security: Code Analysis, Malware Analysis, Reverse Engineering
Large Language Model (LLM) for Software Security: Code Analysis, Malware Analysis, Reverse Engineering
Hamed Jelodar
Samita Bai
Parisa Hamedi
Hesamodin Mohammadian
R. Razavi-Far
Ali Ghorbani
263
25
0
07 Apr 2025
Updating Windows Malware Detectors: Balancing Robustness and Regression against Adversarial EXEmples
Updating Windows Malware Detectors: Balancing Robustness and Regression against Adversarial EXEmplesComputers & security (Comput. Secur.), 2024
M. Kozák
Christian Scano
Dmitrijs Trizna
Fabio Roli
AAML
302
1
0
04 May 2024
1
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