Dataset of attacks on a live enterprise VoIP network for machine learning based intrusion detection and prevention systems

Christabelle Alvares, Dristi Dinesh, Syed Alvi, Tannish Gautam, Maheen Hasib, Ali Raza

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

This data article presents a dataset which can be used to train machine learning (ML) algorithms towards intrusion detection and prevention systems (IDS/IPS). The dataset applies to the field of unified communications in voice over internet protocol (VoIP) networks. Information related to the design and implementation of a real enterprise VoIP network is provided along with the specific protocols used. The attack tools used to disrupt the VoIP communications and the resulting data collected are uniquely presented in sub-datasets. Guidance on how to use the dataset and benefit from the raw packet captures is provided to support research and development in IDS/IPS systems.
Original languageEnglish
Article number108283
JournalComputer Networks
Volume197
Early online date6 Jul 2021
DOIs
Publication statusPublished - 9 Oct 2021

Fingerprint

Dive into the research topics of 'Dataset of attacks on a live enterprise VoIP network for machine learning based intrusion detection and prevention systems'. Together they form a unique fingerprint.

Cite this