Published May 27, 2026 | Version v1

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

  • 1. KIOS Research and Innovation Center of Excellence, University of Cyprus
  • 2. Department of Electrical and Computer Engineering, University of Cyprus
  • 3. Algolysis Ltd

Description

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.

Files

SmartHome_RealLife_TB.csv

Files (123.8 kB)

Name Size Download all
md5:f7a43a893df24ce6025242769d433f35
116.9 kB Preview Download
md5:6d20124e2edab0f3b04ea3d0ae176a72
6.9 kB Preview Download

Additional details

Funding

European Commission
KIOS CoE - KIOS Research and Innovation Centre of Excellence 739551