A Foray Into Extracting Malicious Features from Executable Code with Neural Network Salience

被引：0

作者：

Santacroce, Michael ^{[1
]}

Stegner, Wayne ^{[1
]}

Koranek, Daniel ^{[2
]}

Jha, Rashmi ^{[1
]}

机构：

[1] Univ Cincinnati, Dept EECS, Cincinnati, OH 45221 USA

[2] Air Force Res Lab, Sensors Directorate, Dayton, OH USA

来源：

PROCEEDINGS OF THE 2019 IEEE NATIONAL AEROSPACE AND ELECTRONICS CONFERENCE (NAECON) | 2019年

关键词：

Neural Networks; Malware Detection; Feature Extraction; Neural Network Salience;

D O I：

暂无

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

We have previously created successful neural networks for malware detection. Here, we examine a network with salience to extract parts of an input deemed important. We show that the blocks we extract are what is important to the network, are unique to their class, and show clear similarities when clustered.

引用

页码：185 / 191

页数：7

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