As the network has expanded considerably, security mechanisms are a key issue in networks. Intrusive activities, such as unauthorized access and data manipulation, are increasing. Therefore, the role of the Network Intrusion Detection System (NIDS) in monitoring network traffic for activity and determining whether an intrusion has occurred is very important. The performance of an IDS depends on the selection of the classification model and training data, however, many classifiers generate similar results when measuring performance. The technique of order of preference for similarity to the ideal solution (TOPSIS) is used to select one or more alternatives based on the criteria. The main objective is to present some classification models used in a data set to select the best alternative according to the performance criteria using the TOPSIS method. The deductive method and selection research technique were applied to study the NSL-KDD.
|Title of host publication||Human Interaction, Emerging Technologies and Future Applications III - Proceedings of the 3rd International Conference on Human Interaction and Emerging Technologies|
|Subtitle of host publication||Future Applications, IHIET 2020|
|Editors||Tareq Ahram, Redha Taiar, Karine Langlois, Arnaud Choplin|
|Number of pages||7|
|State||Published - 2021|
|Event||3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020 - Paris, France|
Duration: 27 Aug 2020 → 29 Aug 2020
|Name||Advances in Intelligent Systems and Computing|
|Conference||3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020|
|Period||27/08/20 → 29/08/20|
Bibliographical noteFunding Information:
Acknowledgments. This work has been supported by the GIIAR research group and the Salesian Polytechnic University of Guayaquil.
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.
Copyright 2020 Elsevier B.V., All rights reserved.
- Intrusion Detection System (IDS)
- Machine learning