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Machine Learning Algorithms for Network Intrusion Detection

Jie Li, Yanpeng Qu, Fei Chao, Hubert P. H. Shum, Edmond S. L. Ho and Longzhi Yang
AI in Cybersecurity, 2019

 Citation: 51#

Machine Learning Algorithms for Network Intrusion Detection
# According to Google Scholar 2023"


Network intrusion is a growing threat with potentially severe impacts, which can be damaging in multiple ways to network infrastructures and digital/intellectual assets in the cyberspace. The approach most commonly employed to combat network intrusion is the development of attack detection systems via machine learning and data mining techniques. These systems can identify and disconnect malicious network traffic, thereby helping to protect networks. This chapter systematically reviews two groups of common intrusion detection systems using fuzzy logic and artificial neural networks, and evaluates them by utilizing the widely used KDD 99 benchmark dataset. Based on the findings, the key challenges and opportunities in addressing cyberattacks using artificial intelligence techniques are summarized and future work suggested.





 author={Li, Jie and Qu, Yanpeng and Chao, Fei and Shum, Hubert P. H. and Ho, Edmond S. L. and Yang, Longzhi},
 booktitle={AI in Cybersecurity},
 title={Machine Learning Algorithms for Network Intrusion Detection},
 publisher={Springer International Publishing},


AU  - Li, Jie
AU  - Qu, Yanpeng
AU  - Chao, Fei
AU  - Shum, Hubert P. H.
AU  - Ho, Edmond S. L.
AU  - Yang, Longzhi
T2  - AI in Cybersecurity
TI  - Machine Learning Algorithms for Network Intrusion Detection
PY  - 2019
SP  - 151
EP  - 179
DO  - 10.1007/978-3-319-98842-9_6
SN  - 978-3-319-98842-9
PB  - Springer International Publishing
ER  - 

Plain Text

Jie Li, Yanpeng Qu, Fei Chao, Hubert P. H. Shum, Edmond S. L. Ho and Longzhi Yang, "Machine Learning Algorithms for Network Intrusion Detection," in AI in Cybersecurity, pp. 151-179, Springer International Publishing, 2019.

Supporting Grants

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Alan Godfrey, Victoria Hetherington, Hubert P. H. Shum, Paolo Bonato, Nigel Lovell and Sam Stuart, "From A to Z: Wearable Technology Explained", Maturitas, 2018



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