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

摘要

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.