Index of /publicDatasets/IoT-23-Dataset-v2/CTU-Honeypot-Capture-7-1

	Name	Last modified	Size	Description
	Parent Directory		-
	2019-07-03-15-15-47-192.168.1.158-labels.config	2022-11-18 18:42	1.5K
	2019-07-03-15-15-47-192.168.1.158-zeek-conn-log.labeled	2024-01-21 15:02	1.2G
	README.html	2022-11-18 13:38	2.6K
	README.md	2022-11-18 12:09	2.2K
	pcap/	2022-11-25 12:10	-
	zeek-labeled/	2022-11-28 10:19	-

IoT-23v2 CTU-Honeypot-Capture-7-1

Device and Type of Traffic

• Type of Capture: benign
• Name: Somfy Door Lock
• Device: IoT device, Somfy Door Lock
• MD5: -
• SHA1: -
• SHA256: -
• VirusTotal: -
• HybridAnalysis: -

Network Capture Information

• Start Date: 2018-07-20
• Duration: 24 hrs
• Size: 897 MB
• Host IP: 192.168.100.108
• Gateway IP: 192.168.100.1
• Number of packets: 11485156

Description of Files

• pcap: original raw network data packets in pcap format.
• zeek-conn.log.labeled: raw flow data generated by the Zeek tool from the pcap file with expert labels.
• labels.config: Rules used to label this capture.
• README.md: Readme file

Labels

This dataset was labeled by hand by security experts by analyzing the traffic and creating labeling rules. The program used was https://github.com/stratosphereips/netflowlabeler. The labels rules in the file labels.config condense all the information needed to understand the labels in this capture.

Additional Files

For additional files associated with this capture visit our Malware Dataset Website: https://mcfp.felk.cvut.cz/publicDatasets/IoT-23v2

About IoT-23v2 Dataset

This capture is part of the IoT-23v2 dataset, a dataset of network traffic from Internet of Things (IoT) devices. It has 20 malware captures executed in IoT devices, and 8 benign captures from IoT devices. It was first published as ‘IoT-23’ (now called IoT-23v1) in January 2020. The network traffic was captured in the Stratosphere Laboratory, AIC group, CTU University in Prague, Czech Republic. Its goal is to offer a large and curated dataset of real and labeled IoT traffic for researchers to develop machine learning algorithms. This dataset and its research was funded by Avast Software. Malware was allow to connect to the Internet. Version 2 has the same traffic as v1, but it is an improved version with much better labels, file’s organization, and a separation of the original 3 benign captures into 8.

Contact and citation

Any question feel free to contact us at aposemat@aic.fel.cvut.cz. For information on how to cite this dataset check the iot-23 site.