MTA-KDD'19 (Malware Traffic Analysis Knowledge Dataset 2019)

恶意软件流量分析知识数据集 2019 (MTA-KDD'19) 是一个更新和完善的数据集，专门用于训练和评估基于机器学习的恶意软件流量分析算法。为了生成它，作者从在线可用的最大网络流量捕获数据库开始，派生具有一组广泛适用的特征的数据集，然后对其进行清理和预处理以去除噪声、处理丢失的数据并保持其大小尽可能小.生成的数据集不受任何特定应用程序的影响（尽管专门针对机器学习算法），并且整个过程可以自动运行以保持更新。

The Malware Traffic Analysis Knowledge Dataset 2019 (MTA-KDD'19) is an updated and refined dataset specifically dedicated to training and evaluating machine learning-based malware traffic analysis algorithms. To create this dataset, the authors started from the largest publicly available network traffic capture database, derived a dataset with a broad set of widely applicable features, then performed cleaning and preprocessing to remove noise, handle missing data, and minimize its overall size as much as possible. The resulting dataset is not restricted to any specific application scenario (though it is specifically tailored for machine learning algorithms), and the entire generation workflow can be automated to support continuous updates.

搜集汇总

背景与挑战

背景概述

MTA-KDD'19是一个专门用于恶意软件流量分析的机器学习数据集，经过清理和预处理以优化算法性能。该数据集由拉奎拉大学于2020年发布，支持自动化更新。