Adversarial Malware Generation in Linux ELF Binaries via Semantic-Preserving Transformations
Malware development and detection have undergone significant changes in recent years as modern concepts, such as machine learning, have been used for both adversarial attacks and defense. Despite intensive research on Windows Portable Executable (PE) files, there is minimal work on Linux Executable and Linkable Format (ELF). In this work, we summarize the academic papers submitted in this field and develop a new adversarial malware generator for the ELF format. Using a variety of metrics, we thoroughly evaluated our generator and achieved an Evasion Rate of 67.74 % while changing the confidence of the malware detector by -0.50 in the mean case for the dataset used. In our approach, we cho...
| Authors | Lukáš Hrdonka, Martin Jureček |
|---|---|
| Primary category | cs.CR |
| Published | 24 April 2026 |
| Last updated at source | 24 April 2026 |
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