Energy-Aware Smart Home Real-Life Testbed Dataset for Fault and Attack Classification in IoT-Based CPS

Overview File SmartHome_RealLife_TB.csv Total instances 788 Features 25 (+ 1 class label column) Source Real-time testbed — TCP packet capture via Wireshark This dataset was collected from a real-time testbed implementation of an Energy Aware Smart Home (EASH) system, as described in: G. Tertytchny, N. Nicolaou, and M. K. Michael, "Classifying network abnormalities into faults and attacks in IoT-based cyber physical systems using machine learning", Submitted to Elsevier. The dataset supports a supervised machine learning framework for differentiating between component faults and network attacks in IoT-based Cyber Physical Systems (CPS), based on communication channel characteristics extracted from TCP traffic.数据集概述 文件：SmartHome_RealLife_TB.csv 总样本量：788 特征维度：25项（含1个类别标签列） 数据来源：实时测试床——通过Wireshark抓取TCP报文 本数据集采集自能源感知智能家居（Energy Aware Smart Home, EASH）系统的实时测试床部署，相关细节参见如下文献： G. Tertytchny、N. Nicolaou 与 M. K. Michael，《利用机器学习对物联网信息物理系统中的网络异常进行故障与攻击分类》，已提交至Elsevier出版社。 该数据集可支撑面向物联网信息物理系统（Cyber Physical Systems, CPS）的监督机器学习框架，能够基于从TCP流量中提取的通信信道特征，区分该系统中的组件故障与网络攻击。