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IoEd-Net: Internet of Educational Things Dataset for Academic Network Analysis

IoT Security & Intrusion Detection Educational IoT / Network Security
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Catalog Summary

"Comprehensive IoT network traffic dataset from an academic environment with 202,085 labeled records capturing benign and malicious activities for cybersecurity and anomaly detection research."

Catalog Notes

Dataset Overview

The IoEd-Net dataset provides detailed network traffic data generated by IoT-enabled devices deployed in an academic network environment. It includes more than 202,000 records of device interactions, covering both benign and malicious activities.

Key Features

  • Source and destination IPs, ports, and geolocation information.
  • Packet-level metrics such as sizes, inter-arrival times, flow duration, and byte counts.
  • Device telemetry including CPU usage, memory consumption, energy usage, and device uptime.
  • Protocol information for TCP, UDP, and ICMP traffic.
  • Labeled benign and malicious flows suitable for supervised learning.

Use Cases

Ideal for research in IoT malware detection, anomaly detection, traffic classification, and academic network cybersecurity.

Data Format

CSV files containing 55 core features and additional derived features for advanced analysis of IoT network behavior.

View Data Structure

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

Preview on Kaggle

Provided Citation

University of New Brunswick (2024). IoEd-Net: Internet of Educational Things Dataset for Academic Network Analysis. Kaggle.

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Source metadata: Kaggle (2026)

Indexed by IoTDataset.com on Jan 20, 2026

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Confirm the licence, version, access conditions, file format, and provenance at the source before use.

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