Abstract
"1,191,264 network intrusion instances with 47 features. Large-scale dataset for training predictive models to detect IoT network attacks and anomalies."
Description
Dataset Overview
Massive IoT intrusion detection dataset containing over 1.19 million instances of network traffic, each characterized by 47 distinct features.
Dataset Statistics
- Total Instances: 1,191,264
- Features: 47 network characteristics
- Attack Types: Multiple categories
- File Format: CSV
Features Include
Protocol types, packet information, connection states, service types, flag indicators, byte counts, duration metrics, error rates, and behavioral patterns.
Applications
Ideal for training deep learning models for intrusion detection, anomaly detection systems, network security analytics, and IoT threat classification.
📊 View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on Kaggle.
Preview on Kaggle
Cite This Dataset
Subhadeep Chakraborty (2023). IoT Intrusion Detection - Network Attack Dataset. [Dataset]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/6142327
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Original source: Kaggle (2023). Visit official page for more details.
Indexed by IoTDataset.com on Jan 21, 2026
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