The VNF cybersecurity dataset for research (VNFCYBERDATA)

Virtualisation has received widespread adoption and deployment across a wide range of enterprises and industries throughout the years. Network Function Virtualisation (NFV) is a technical concept that presents a method for dynamically delivering virtualised network functions as virtualised or software components. Virtualised Network Function (VNF) has distinct advantages, but it also faces serious security challenges. Cyberattacks such as Denial of Service (DoS), malware/rootkit injection, port scanning, and so on can target VNF appliances just like any other network infrastructure. To create exceptional training exercises for machine or deep learning (ML/DL) models to combat cyberattacks in VNF, a suitable dataset (VNFCYBERDATA) exhibiting an actual reflection, or one that is reasonably close to an actual reflection, of the problem that the ML/DL model could address is required. This article describes a real VNF dataset that contains over seven million data points and twenty-five cyberattacks generated from five VNF appliances. To facilitate a realistic examination of VNF traffic, the dataset includes both benign and malicious traffic.CitationIf you are using this dataset for your research, please reference it as"Ayodele, B.; Buttigieg, V. The VNF Cybersecurity Dataset for Research (VNFCYBERDATA). Data 2024, 9, 132. https://doi.org/10.3390/data9110132"DocumentationDataset documentation is available at: https://www.mdpi.com/2306-5729/9/11/132

虚拟化技术在多年间已被广泛采纳并部署于众多企业及行业中。网络功能虚拟化（NFV）作为一种技术理念，提供了一种动态交付虚拟化网络功能的方法，这些功能以虚拟化或软件组件的形式呈现。虚拟化网络功能（VNF）具备独特的优势，然而，它亦面临着严峻的安全挑战。诸如拒绝服务（DoS）、恶意软件/根kit注入、端口扫描等网络攻击可能针对VNF设备，正如其他任何网络基础设施一样。为了创建针对VNF中网络攻击的机器或深度学习（ML/DL）模型的卓越训练练习，需要一套合适的（VNFCYBERDATA）数据集，该数据集能够真实反映，或与真实情况相当接近，机器/深度学习模型可能解决的网络安全问题。本文描述了一个真实的VNF数据集，其中包含超过七百万个数据点和由五个VNF设备生成的二十五种网络攻击。为了便于对VNF流量的现实检验，该数据集包含了良性及恶意流量。如若您在使用此数据集进行研究，请引用如下：'Ayodele, B.; Buttigieg, V. The VNF Cybersecurity Dataset for Research (VNFCYBERDATA). Data 2024, 9, 132. https://doi.org/10.3390/data9110132'。数据集文档可在以下链接查阅：https://www.mdpi.com/2306-5729/9/11/132