Study of Intrusion Detection System using Machine Learning Approach
Keywords:
Intrusion Detection System, Machine Learning, Network Intrusion Detection SystemAbstract
Due to the expansion and development of modern networks, the volume and destructiveness of cyber-attacks are continuously increasing. Intrusion Detection Systems (IDSs) are essential techniques for maintaining and enhancing network security. IDS-ML is an open-source code repository written in Python for developing IDSs from public network traffic datasets using traditional and advanced Machine Learning (ML) algorithms. 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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