IoT Intrusion Detection

Subhadeep Chakraborty

doi:10.34740/KAGGLE/DSV/6142327

Kaggle

IoT Intrusion Detection - Network Attack Dataset

IoT Security & Intrusion Detection Cybersecurity

Jan 21, 2026

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Catalog Summary

"1,191,264 network intrusion instances with 47 features. Large-scale dataset for training predictive models to detect IoT network attacks and anomalies."

Catalog Notes

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.

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Cite This Dataset

Subhadeep Chakraborty (2023). IoT Intrusion Detection. [Dataset]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/6142327

Source metadata: Kaggle (2023) · DOI: 10.34740/KAGGLE/DSV/6142327

Indexed by IoTDataset.com on Jan 21, 2026

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