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Detection of Network Anomalies with Machine Learning Methods | IEEE Conference Publication | IEEE Xplore
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Detection of Network Anomalies with Machine Learning Methods


Abstract:

The present study, aimed to detect cyber-attacks, and unexpected access requests on devices in the telecommunication networks, enabling the necessary measures to be taken...Show More

Abstract:

The present study, aimed to detect cyber-attacks, and unexpected access requests on devices in the telecommunication networks, enabling the necessary measures to be taken early. With K-Nearest Neighbors (KNN) and Naive Bayes machine learning methods, predicted whether the raw data packets contain cyber-attack according to different properties of these packets using the UNSW-NB15 dataset. KNN algorithms with different K values and the Naive Bayes method were compared according to accuracy rates and the results were given in the table. As a result, changes in accuracy rates were observed according to different k neighbor values in the KNN algorithm. Higher accuracy rates than Naive Bayes were achieved in the models created with the KNN algorithm.
Date of Conference: 06-07 June 2022
Date Added to IEEE Xplore: 22 June 2022
ISBN Information:
Conference Location: Istanbul, Turkey

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