Samardziska, Anastasija and Martinovska Bande, Cveta (2022) Network intrusion detection based on classification. Balkan Journal of Applied Mathematics and Informatics, 5 (2). pp. 57-67. ISSN 2545-4803
Full text not available from this repository.Abstract
Network security is a serious concern for information technology users. Intrusion detection
systems can detect malicious traffic and suspicious activity looking for signatures of known attacks.
This paper describes a network intrusion detection system based on the deep learning approach. The
system uses the ability of the neural network to detect attacks for which the system was not explicitly
trained. The proposed solution can effectively identify network attacks with the accuracy of 98%
tested on the NSL_KDD dataset. The paper analyzes the impact of transformation functions applied
to the features of the dataset.
| Item Type: | Article |
|---|---|
| Subjects: | Natural sciences > Computer and information sciences |
| Divisions: | Faculty of Computer Science |
| Depositing User: | Cveta Martinovska Bande |
| Date Deposited: | 04 Feb 2023 20:21 |
| Last Modified: | 04 Feb 2023 20:21 |
| URI: | https://eprints.ugd.edu.mk/id/eprint/31303 |
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