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External Dataset
External Data Source
56 (lowest rank is 56)

Category & Restrictions

cyber defense, intrusion detection


Machine Learning based Intrusion Detection Systems are difficult to evaluate due to a shortage of datasets representing accurately network traffic and their associated threats.

In this project we attempt at solving this problem by presenting two taxonomies    A Taxonomy and Survey of Intrusion Detection System Design Techniques, Network Threats and Datasets    and    A Taxonomy of Malicious Traffic for Intrusion Detection Systems , classifying threats as well as evaluating current datasets.

The result shows that a large portion of current research published train IDS algorithms against outdated datasets and outdated threats. To this end, we provide the source ofour threat taxonomy, allowing other researchers to contribute and modify it. The taxonomy is a collaboration between Abertay University, The University of Strathclyde, The Naval Academy Research Institute and Middlesex University (Mauritius Campus)

The taxonomy classifies each network threat according to:
Its Source (i.e. Networking, Host, Software, Hardware, Human)
OSI Layer
Active / Passive

We have released a pre-print of our article on Arxiv, it includes the original taxonomies in a paper called
A Taxonomy and Survey of Intrusion Detection System Design Techniques, Network Threats and Datasets

Additional Details

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