Mal2d: 2d Based Deep Learning Model for Malware Detection Using Black and White Binary Image
-
- CHO Minkyoung
- Dept. of Computer Eng., Myongji Univ.
-
- KIM Jik-Soo
- Dept. of Computer Eng., Myongji Univ.
-
- SHIN Jongho
- Dept. of Computer Eng., Myongji Univ.
-
- SHIN Incheol
- Dept. of Computer Eng., Mokpo Nat'l Univ.
抄録
<p>We propose an effective 2d image based end-to-end deep learning model for malware detection by introducing a black & white embedding to reserve bit information and adapting the convolution architecture. Experimental results show that our proposed scheme can achieve superior performance in both of training and testing data sets compared to well-known image recognition deep learning models (VGG and ResNet).</p>
収録刊行物
-
- IEICE Transactions on Information and Systems
-
IEICE Transactions on Information and Systems E103.D (4), 896-900, 2020-04-01
一般社団法人 電子情報通信学会
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1390002184890924672
-
- NII論文ID
- 130007824969
-
- ISSN
- 17451361
- 09168532
-
- 本文言語コード
- en
-
- データソース種別
-
- JaLC
- Crossref
- CiNii Articles
-
- 抄録ライセンスフラグ
- 使用不可