IoT Emulated ICMP/Ping Dataset — Normal and Malicious Traffic [3.2 GB PCAP]
Abstract
"IoT IDS dataset for distinguishing normal and malicious ICMP/Ping traffic generated from an ESP-01s embedded device. PCAP, Zeek logs, and labelled CSV files."
Description
Overview
This Zenodo dataset provides normal and malicious ICMP/Ping traffic generated from an embedded IoT device. It is explicitly related to intrusion detection systems, computer network traffic, and IoT security.
The data generation sequence starts with raw PCAP network traffic generated by an ESP-01s device. The PCAP files are then transformed into Zeek log files, and the logs are extracted into labelled CSV files prepared for machine-learning analysis.
The dataset is useful for studying ICMP flood and Ping flood behaviour in lightweight IoT environments and for evaluating ML-based detection of malicious ICMP/Ping activity.
Column Schema
| Column | Description |
|---|---|
| pcap_file | Raw ICMP/Ping packet-capture file generated from the ESP-01s device. |
| zeek_log | Zeek log extracted from the raw PCAP traffic. |
| csv_record | Labelled CSV record derived from Zeek log extraction. |
| traffic_type | Normal or malicious ICMP/Ping traffic category. |
| label | Machine-learning label used to distinguish normal and malicious traffic. |
Key Statistics
- Total Records: Labelled CSV files extracted from Zeek logs; row count not specified on the Zenodo page
- Features: Zeek-derived flow information for ICMP/Ping traffic
- File Format: PCAP, Zeek logs, CSV
- File Size: Raw PCAP archive 3.2 GB; Zeek logs 1.4 MB; extracted CSV dataset 8.8 kB
- Time Period: Published March 26, 2023; modified July 4, 2023
- Device: ESP-01s embedded IoT device
Use Cases
- ICMP/Ping flood intrusion detection
- Embedded IoT traffic classification
- Zeek-to-CSV feature extraction workflows
- Machine-learning evaluation for lightweight IoT network attacks
Source & Attribution
Created by Omar Almorabea, Tariq Khanzada, Muhammad Aslam, Fatheah Hendi, and Ahmad Almorabea. Published on Zenodo with DOI 10.5281/zenodo.7772015 and licensed under CC BY 4.0.
View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on Zenodo.
Preview on ZenodoCite This Dataset
Almorabea, Omar, Khanzada, Tariq, Aslam, Muhammad, Hendi, Fatheah, & Almorabea, Ahmad (2023). IoT Emulated ICMP/Ping Dataset — Normal and Malicious Traffic [3.2 GB PCAP]. [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.7772015
Source: Zenodo (2023) · DOI: 10.5281/zenodo.7772015
Indexed by IoTDataset.com on Jun 02, 2026
Ready to Start Your Research?
Download this dataset directly from the official repository and start building your next breakthrough project.