The scope of our review study is to provide a brief idea of intrusion detection as well as a reference to other research works done in the field of machine learning based intrusion detection system. Also, the results obtained from the various works such as evaluated metrics, datasets, and accuracy are discussed and compared. This paper presents a literary review of various works on different machine learning-based intrusion detection system presented in different research papers over the last five years. ![]() But the major issue remains with the presence of vast diversity of features that leads to lengthy training processes and the need to deal with the prediction accuracy. To cope with such issues, researchers have come up with various methods of machine learning based techniques in order to detect malicious activity on the network. Cyber threats in the form of malicious software or also known as “malwares” have posed a serious threat to the smooth running of both government and business sectors. This results in the increase of exposure to different cyber-attacks on the network infrastructures. ![]() As a result of the current global pandemic, there has been a surge in the use of various online platforms and services available via the internet.
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