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Paper · arXiv

Bytes to Threats: Byte-Sequence Transformer For Malware Detection

Existing malware detection approaches heavily rely on handcrafted features derived from static or dynamic analysis of the executable files. These methods require specialized domain expertise, dedicated analysis tools, and time-consuming analysis, which limits their scalability and robustness in the face of the increasing complexity and diversity of modern malware. Consequently, there is a growing interest in approaches that operate directly on raw bytes, which contain rich semantic and structural information. However, capturing long-range dependencies within executable files remains challenging for conventional static and CNN-based methods. This paper presents MalwareFormer, a transformer...

AuthorsAbdelrahman Yassin Eljamal, Abdeltawab Hendawi
Primary categorycs.CR
Published13 October 2026
Last updated at source13 October 2026
cs.CRcs.AI
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