Edge IIoT Network Traffic for Cyber Attack Detection

Edge-IIoTset contains network traffic data from an Industrial Internet of Things testbed. The dataset is designed for cybersecurity research, specifically for detecting and classifying cyber attacks in industrial control systems. It originates from the OpenML platform with contributions focused on IoT security.

Use Cases

• Classify attack types using labeled network traffic features.
• Detect anomalies in industrial IoT network behavior patterns.
• Train models to distinguish normal operations from malicious activities like DDoS or data injection.
• Benchmark machine learning algorithms for IoT security on tabular network data.

Strengths

• Dataset is specifically designed for a critical domain: industrial IoT cybersecurity.
• Includes labels for multiple cyber attack categories relevant to industrial control systems.

Limitations

• Specific row count, column count, and data completeness are unknown.
• The temporal range and data collection frequency are not specified.
• Potential class imbalance in attack categories is unverified.

Provenance

Source

OpenML

Collection Method

Collected from an Industrial IoT testbed network, likely involving simulated or captured traffic.