ToN IoT Linux Datasets

ToN IoT Linux Datasets是由新南威尔士大学堪培拉分校的研究团队开发的一套数据集，旨在为评估AI驱动的安全应用提供异构和可扩展的数据源。该数据集包含从物联网服务、操作系统和网络流量中收集的分布式数据源。创建过程中，采用了三层分布式架构（边缘、雾、云），通过软件定义网络和网络功能虚拟化技术控制数据收集。数据集主要用于训练和验证如入侵检测、威胁情报、隐私保护和数字取证等AI驱动的安全解决方案，解决物联网环境中的安全问题。

ToN IoT Linux Datasets is a dataset developed by a research team from the University of New South Wales Canberra, aiming to provide heterogeneous and scalable data sources for evaluating AI-driven security applications. This dataset encompasses distributed data sources collected from IoT services, operating systems and network traffic. During its development, a three-tier distributed architecture (edge, fog, cloud) was adopted, with data collection controlled via software-defined networking and network function virtualization technologies. The dataset is primarily used for training and validating AI-driven security solutions such as intrusion detection, threat intelligence, privacy protection and digital forensics, to address security issues in IoT environments.

搜集汇总

背景与挑战

背景概述

ToN IoT Linux Datasets是由新南威尔士大学堪培拉分校研究团队开发的物联网安全数据集，旨在为AI驱动的安全应用评估提供异构和可扩展的数据源。它采用三层分布式架构收集来自物联网服务、操作系统和网络流量的数据，主要用于训练和验证入侵检测、威胁情报等解决方案，以解决物联网环境中的安全问题。