With the ubiquitous nature of information technology solutions that
facilitate communication in the modern world, cyber attacks are increasing in
volume and becoming more sophisticated in nature. From classic network-based
Denial of Service (DoS) attacks to the more recent concerns of privacy
compromises, Intrusion Detection Systems (IDS) are becoming an urgent need to
safeguard the modern information technology landscape. The development of these
IDS relies on training and evaluation datasets that must evolve with time and
represent the contemporary threat landscape. The purpose of this analysis is to
explore such recent datasets, describe how they enable research endeavours and
the development of novel IDS. Specifically, 7 recent datasets published for IDS
research have been reviewed along with selected publications that have employed
them. In doing so, the discussion emphasizes the need for the publication of
even more modern datasets, especially for emerging technologies such as the
Internet of Things (IoT) and smartphone devices, to ensure that modern networks
and communication channels are secured. Furthermore, a taxonomy based on the
discussed datasets has been developed that can be used to inform the dataset
selection process for future research endeavours.

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