Research Article
Elimination of Network Intrusion Using Advance Data Mining Technology
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@INPROCEEDINGS{10.1007/978-3-031-04409-0_15, author={Dhulfiqar Saad Jaafar and Hoshang Kolivand}, title={Elimination of Network Intrusion Using Advance Data Mining Technology}, proceedings={Machine Learning and Intelligent Communications. 6th EAI International Conference, MLICOM 2021, Virtual Event, November 2021, Proceedings}, proceedings_a={MLICOM}, year={2022}, month={5}, keywords={Network intrusion Data mining Machine learning FFNN KDD K-means DB Scan Intrusion Attack}, doi={10.1007/978-3-031-04409-0_15} }- Dhulfiqar Saad Jaafar
Hoshang Kolivand
Year: 2022
Elimination of Network Intrusion Using Advance Data Mining Technology
MLICOM
Springer
DOI: 10.1007/978-3-031-04409-0_15
Abstract
Advancements of data mining and machine learning have paved the road for establishing an efficient attack prediction paradigm to protect large scaled networks. In this study, computer network intrusions had been eliminated using smart machine learning algorithm to eliminate network intrusion. Referring a big dataset named KDD computer intrusion dataset which includes large number of connections that diagnosed with several types of attacks; the model is established for predicting the type of attack by learning through this data. Feed forward neural network model is outperformed over the other proposed clustering models in attack prediction accuracy.
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