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Survey of Intrusion Detection of Imbalanced Network based on Machine Learning Algorithm
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 185 - Number 23 |
| Year of Publication: 2023 |
| Authors: Rachita Kulshrestha, Chetan Gupta, Ritu Shrivastava |
10.5120/ijca2023922980
|
Rachita Kulshrestha, Chetan Gupta, Ritu Shrivastava . Survey of Intrusion Detection of Imbalanced Network based on Machine Learning Algorithm. International Journal of Computer Applications. 185, 23 ( Jul 2023), 27-32. DOI=10.5120/ijca2023922980
Abstract
Intrusion detection is the process of analyzing the network packets to identify if the packet is legitimate or anomalous. The major challenges involved in this domain includes the huge volume of data for training and the fast and streaming data that is to be provided for the prediction process. The accuracy and timely detection should be ensured by Network Intrusion Detection System (NIDS). For intrusion detection in balance and imbalance network traffic, machine learning and deep learning methods can be used. In this paper a survey of different intrusion detection systems based on machine learning and deep learning methods is performed. The proposed system adds on ensemble learning approach to improve accuracy. A review on various intrusion detection system (IDS) using the techniques in machine learning is been put forwarded.
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