Intrusion Detection System Using Machine Learning: An Algorithm Study

Yadgude Samrudhi Ravindra

Intrusion Detection System Using Machine Learning: An Algorithm Study

Author : Yadgude Samrudhi Ravindra Journa Name: INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH AND ENGINEERING TRENDS Country : India Volume: 9 issue: 6 Year: 2023 Views : 383

Abstract:

Machine Learning is an evolving domain in the field of technology. Its algorithms are capable of detecting various patterns, making decisions based on them and adapting to an environment that is dynamic. In today’s digitally interconnected landscape, the surge in cyber threats necessitates innovative approaches to fortify network security. Cyber security demands an Intrusion detection system to safeguard networks from evolving threats. This research delves into an advanced exploration of four intrusion detection methods—Autoencoders, Support Vector Machines (SVM), XG Boost, and Principal Component Analysis (PCA) coupled with a classifier. Going beyond the conventional analysis, this study not only explains the specific scenarios conducive to each method but also unveils the intricacies of their applicability, providing a deep understanding of when to deploy these techniques based on their advanced advantages and potential limitations.