Automatic Malware Detection Using Deep Learning Based on Static Analysis

被引：7
|
作者：
Liu, Liu [1 ]
Wang, Baosheng [1 ]
机构：
[1] Natl Univ Def Technol, Sch Comp, Changsha 410073, Hunan, Peoples R China
来源：
DATA SCIENCE, PT 1 | 2017年 / 727卷
关键词：
Ensemble learning; K-means; Negative correlation; Neural network; NEURAL-NETWORKS; CLASSIFICATION;
D O I：
10.1007/978-981-10-6385-5_42
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Malware detection is an important challenge in the field of information security. The paper proposes a novel method using deep learning based on static analysis. Deep learning has stronger nonlinear expression ability than shallow learning, so it has received much attention from scholar and manufacturers. We use static analysis to extract the malware features are mapped into the input of deep learning. The experiments show that the method is suitable for detecting malware.
引用
收藏
页码：500 / 507
页数：8
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