Datasets
Standard Dataset
NANCY SNS JU Project - Cyberattacks on O-RAN 5G Testbed Dataset
- Citation Author(s):
-
AthanasiosLiatifis
University of Western MacedoniaDimitriosPliatsiosUniversity of Western MacedoniaIoannisMakrisMetaMind Innovations P.C.NikolaosNtampakisMetaMind Innovations P.C.SotiriosTegosUniversity of Western MacedoniaNikolaosMitsiouUniversity of Western MacedoniaKonstantinosKyranouSidroco Holdings Ltd.ThomasLagkasUniversity of Western MacedoniaPanagiotisSarigiannidisUniversity of Western Macedonia - Submitted by:
- Dimitrios Pliatsios
- Last updated:
- Tue, 10/01/2024 - 06:40
- DOI:
- 10.21227/vjf4-y322
- Data Format:
- License:
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Abstract
This dataset was developed in the context of the NANCY project and it is the output of the experiments involving cyberattacks against services that are running in a 5G coverage expansion scenario. The coverage expansion scenario involves a main operator and a micro-operator which extends the main operator’s coverage and can also provide additional services, such as Artificial Intelligence-based cyberattack detection.
The dataset includes both network traffic which was captured and stored in a .pcap file, as well as an annotated .csv file. The annotated .csv file was generated by parsing the .pcap file through CICFlowMeter to extract the network flows. It was manually annotated based on the timeline of the cyberattacks that were carried out.
The Dataset.7z includes the following two files:
Network_Traffic_Capture.pcap: This file includes all the packets that were captured during the experimentation. Specifically, it contains packets from benign and malicious network traffic. The benign traffic is associated with browsing and video streaming activities, while the malicious traffic is associatesd with the 7 types of attacks that were carried out against the main operator and micro-operator services.
Network_Flows_Annotated.csv: This file is the output of the CICFlowMeter, along with the respective annotations that map the flows to benign traffic or to one of the 7 attacks.
