Intrusion Detection with Machine Learning Using Open-Sourced Datasets

Theodosis Mourouzis; Andreas Avgousti

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arXiv · 2107.12621

Intrusion Detection with Machine Learning Using Open-Sourced Datasets

Theodosis Mourouzis·Andreas Avgousti

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Abstract

No significant research has been conducted so far on Intrusion detection due to data availability since, network traffic within companies is private information and no available logs can be found on the Internet for independent research. This paper aims to answer the question whether open-sourced data, that is usually simulated network traffic can assist in developing a robust model that will effectively recognize and deter possible denial of service or infiltration attacks.

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BibTeX RIS

Theodosis Mourouzis, Andreas Avgousti. 2021-07-27. Intrusion Detection with Machine Learning Using Open-Sourced Datasets. https://arxiv.org/abs/2107.12621

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