A hardware-in-the-loop Secure Water Treatment dataset for cyber-physical security testing

This dataset supports researchers in the validation process of solutions such as Intrusion Detection Systems (IDS) based on artificial intelligence and machine learning techniques for the detection and categorization of threats in Cyber Physical Systems (CPS). To that aim, data have been acquired from a Secure Water Treatment (SWaT) hardware-in-the-loop testbed which emulates water passage between nine tanks via solenoid-valves, pumps, pressure and flow sensors. The testbed is composed by a real partition which is virtually connected to a simulated one. The presented dataset consists of both physical and virtual process measurements in order to highlight the consequences of attacks in the physical process, in control variables as well as in network traffic behavior. Data have been acquired during four different acquisitions for a total of about two hours in normal behaviour and in presence of anomalies induced by different types of physical and/or cyber events.本数据集可辅助研究人员验证基于人工智能与机器学习技术的入侵检测系统（Intrusion Detection Systems, IDS）等解决方案，以实现信息物理系统（Cyber Physical Systems, CPS）内威胁的检测与分类。为此，研究人员从安全水处理（Secure Water Treatment, SWaT）硬件在环试验台采集相关数据，该试验台通过电磁阀、泵、压力传感器与流量传感器模拟9个储罐间的水流传输过程。该试验台由真实分区与虚拟连接的模拟分区共同构成。本数据集同时涵盖物理过程与虚拟过程的测量数据，旨在凸显攻击对物理过程、控制变量及网络流量行为所产生的影响。数据采集自四次独立的采集环节，总时长约两小时，覆盖正常运行状态，以及由不同类型物理和/或网络事件诱发的异常运行场景。

搜集汇总

背景与挑战

背景概述

该数据集是一个硬件在环水分布测试台数据集，专为网络物理安全测试设计，用于验证基于人工智能和机器学习的入侵检测系统。它包含正常和异常行为下的物理和网络测量数据，模拟了水传输过程中的多种攻击场景，支持威胁检测和分类研究。