تقرير
Feature Engineering Using File Layout for Malware Detection
| العنوان: | Feature Engineering Using File Layout for Malware Detection |
|---|---|
| المؤلفون: | Kim, Jeongwoo, Cho, Eun-Sun, Paik, Joon-Young |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Cryptography and Security |
| الوصف: | Malware detection on binary executables provides a high availability to even binaries which are not disassembled or decompiled. However, a binary-level approach could cause ambiguity problems. In this paper, we propose a new feature engineering technique that use minimal knowledge about the internal layout on a binary. The proposed feature avoids the ambiguity problems by integrating the information about the layout with structural entropy. The experimental results show that our feature improves accuracy and F1-score by 3.3% and 0.07, respectively, on a CNN based malware detector with realistic benign and malicious samples. Comment: 2pages, no figures, This manuscript was presented in the poster session of The Annual Computer Security Applications Conference (ACSAC) 2020 |
| نوع الوثيقة: | Working Paper |
| الوصول الحر: | http://arxiv.org/abs/2304.02260Test |
| رقم الانضمام: | edsarx.2304.02260 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |