The VNF Cybersecurity Dataset for Research (VNFCYBERDATA)

Believe Ayodele () and Victor Buttigieg
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Believe Ayodele: Department of Communications and Computer Engineering, Faculty of ICT, University of Malta, Msida MSD 2080, Malta
Victor Buttigieg: Department of Communications and Computer Engineering, Faculty of ICT, University of Malta, Msida MSD 2080, Malta

Data, 2024, vol. 9, issue 11, 1-15

Abstract: Virtualisation has received widespread adoption and deployment across a wide range of enterprises and industries throughout the years. Network Function Virtualisation (NFV) is a technical concept that presents a method for dynamically delivering virtualised network functions as virtualised or software components. Virtualised Network Function (VNF) has distinct advantages, but it also faces serious security challenges. Cyberattacks such as Denial of Service (DoS), malware/rootkit injection, port scanning, and so on can target VNF appliances just like any other network infrastructure. To create exceptional training exercises for machine or deep learning (ML/DL) models to combat cyberattacks in VNF, a suitable dataset (VNFCYBERDATA) exhibiting an actual reflection, or one that is reasonably close to an actual reflection, of the problem that the ML/DL model could address is required. This article describes a real VNF dataset that contains over seven million data points and twenty-five cyberattacks generated from five VNF appliances. To facilitate a realistic examination of VNF traffic, the dataset includes both benign and malicious traffic.

Keywords: virtualised network function; VNF; dataset; cybersecurity; network function virtualisation; NFV (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2024
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