论文标题
Windows PE恶意软件分类的多功能数据集
Multi-feature Dataset for Windows PE Malware Classification
论文作者
论文摘要
本文介绍了用于训练机器学习分类器的多功能数据集，用于检测恶意的Windows Portable可执行文件（PE）文件。该数据集包括来自属于5个恶意软件系列的18,551个二进制样本的四个功能集，包括间谍软件，勒索软件，下载器，后门和通用恶意软件。该功能集包括DLL列表及其功能，PE标头不同字段的值和部分。首先，我们解释数据收集和创建阶段，然后解释如何使用Virustotal的服务标记其中的样本。最后，我们探索数据集，以描述该数据集如何使研究人员受益于静态恶意软件分析。该数据集公开，希望它能帮助激发机器学习研究以进行恶意软件检测。
This paper describes a multi-feature dataset for training machine learning classifiers for detecting malicious Windows Portable Executable (PE) files. The dataset includes four feature sets from 18,551 binary samples belonging to five malware families including Spyware, Ransomware, Downloader, Backdoor and Generic Malware. The feature sets include the list of DLLs and their functions, values of different fields of PE Header and Sections. First, we explain the data collection and creation phase and then we explain how did we label the samples in it using VirusTotal's services. Finally, we explore the dataset to describe how this dataset can benefit the researchers for static malware analysis. The dataset is made public in the hope that it will help inspire machine learning research for malware detection.
