Skip to main content
Nature Scientific Data

ICS-NAD: Network Attack Detection in Industrial Control Systems

Abstract

"A large-scale dataset (245GB) collected from real-world industrial control systems for advanced threat detection."

Description

The ICS-NAD dataset provides a rare and comprehensive look into network traffic within real-world Industrial Control Systems (ICS). Published in 2026, it consists of 245.96 GB of data across 272 files. The collection includes raw network traffic in PCAP format and extracted features in CSV format with precise labels for various cyber-physical attacks. It captures the unique communication patterns of industrial protocols (such as Modbus, S7Comm, and OPC UA) and contrasts normal operational baselines with sophisticated attack vectors targeting industrial sensors and actuators. This dataset is crucial for researchers developing anomaly detection models for Critical Infrastructure Protection (CIP) and Industry 4.0 environments.

📊 View Data Structure

To explore column names, data types, and sample rows, visit the official dataset page on Nature Scientific Data.

Preview on Nature Scientific Data

Cite This Dataset

Zhou, X., & others (2026). ICS-NAD: Network Attack Detection in Industrial Control Systems. Scientific Data. [Dataset]. Nature Scientific Data. https://doi.org/10.1038/s41597-026-06738-x

Select your preferred citation style above. The citation will automatically update and you can copy it to your clipboard.

Original source: Nature Scientific Data (2026). Visit official page for more details.

Indexed by IoTDataset.com on Feb 12, 2026

Ready to Start Your Research?

Download this dataset directly from the official repository and start building your next breakthrough project.

Download Dataset

Related Topics & Keywords

Share This Research

More in Industrial IoT (IIoT)

View All
Industrial IoT UNSW Canberra

ToN_IoT: Telemetry, Operating Systems, and Network Traffic

ToN_IoT is a large-scale dataset featuring heterogeneous data from IoT sensors, operating systems, and network traffic for advanced intrusion detection research in Industry 4.0.

Feb 15, 2026
Industrial IoT Kaggle

Post-Quantum Cryptography Impact in Industrial IoT

Released in October 2025, this dataset captures performance metrics and network traffic associated with implementing Post-Quantum Cryptography (PQC) in Industrial IoT (IIoT) scenarios. It supports research into the feasibility and overhead of quantum-resistant security protocols on resource-constrained industrial hardware.

Feb 06, 2026
Industrial IoT Kaggle

Industrial IoT Synthetic Failure Simulation Dataset

This Industrial IoT dataset provides synthetic yet realistic sensor data simulating equipment operation under normal and various failure conditions. Designed for predictive maintenance and machine learning, it includes sensor specifications, operational thresholds, and failure labels, allowing researchers to develop anomaly detection models without the constraints of sensitive real-world industrial data.

Feb 05, 2026
Industrial IoT / Predictive Maintenance Scientific Reports (Nature)

A Real-World IIoT Dataset for Predictive Maintenance Based on Machine Degradation

A multi-sensor dataset from a real manufacturing environment monitoring CNC machine degradation through vibration, temperature, current, and acoustic emission sensors over a 6-month period.

Feb 04, 2026