Development of a centralized intrusion detection system using machine learning

In the world of Internet many people become victim of cyberattacks. One of the most devastating threats are DoS and DDoS attacks. In this paper is suggested an Intrusion Detection System in which are implemented machine learning models. SVM classification algorithm is used for making three different...

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Main Authors: Rusev, Alexander, Tsochev, Georgi, Trifonov, Roumen
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Denial of service attacks
Intrusion detection systems
Machine learning
Support vector machines
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creator Rusev, Alexander
Tsochev, Georgi
Trifonov, Roumen
description In the world of Internet many people become victim of cyberattacks. One of the most devastating threats are DoS and DDoS attacks. In this paper is suggested an Intrusion Detection System in which are implemented machine learning models. SVM classification algorithm is used for making three different machine learning models. Each machine model has specifically chosen features which characterize a different type of DoS attack. All machine learning models are integrated in the proposed IDS.
doi_str_mv 10.1063/5.0124920
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source American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list)
subjects Algorithms
Denial of service attacks
Intrusion detection systems
Machine learning
Support vector machines
title Development of a centralized intrusion detection system using machine learning
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