Elastic Malware Benchmark for Empowering Researchers 2017 Part 2

The EMBER dataset is a collection of features from PE files that serve as a benchmark dataset for researchers. The EMBER2017 dataset contained features from 1.1 million PE files scanned in or before 2017 and the EMBER2018 dataset contains features from 1 million PE files scanned in or before 2018. This repository makes it easy to reproducibly train the benchmark models, extend the provided feature set, or classify new PE files with the benchmark models. This paper describes many more details about the dataset: # Cite H. Anderson and P. Roth, "EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models”, in ArXiv e-prints. Apr. 2018.

EMBER数据集系由PE文件特征构成的集合，该集合作为研究人员评估基准数据集。EMBER2017数据集包含了在2017年或之前扫描的110万PE文件的特征，而EMBER2018数据集则包含了在2018年或之前扫描的100万PE文件的特征。本仓库旨在简化基准模型的复现训练、扩展现有特征集或使用基准模型对新PE文件进行分类的过程。本文详细描述了数据集的诸多细节：[引用 H. Anderson 和 P. Roth, “EMBER：一个用于训练静态PE恶意软件机器学习模型的开放数据集”，载于ArXiv电子预印本，2018年4月]。