Can, Duy Cat and Le, Hoang Quynh and Ha, Quang Thuy (2021) Detection of Distributed Denial of Service Attacks Using Automatic Feature Selection with Enhancement for Imbalance Dataset. In: ACIIDS 2021: Intelligent Information and Database Systems. Springer, pp. 386-398.
Full text not available from this repository.Abstract
With the development of technology, the highly accessible internet service is the biggest demand for most people. Online network, however, has been suffering from malicious attempts to disrupt essential web technologies, resulting in service failures. In this work, we introduced a model to detect and classify Distributed Denial of Service attacks based on neural networks that take advantage of a proposed automatic feature selection component. The experimental results on CIC-DDoS 2019 dataset have demonstrated that our proposed model outperformed other machine learning-based model by large margin. We also investigated the effectiveness of weighted loss and hinge loss on handling the class imbalance problem.
| Item Type: | Book Section |
|---|---|
| Subjects: | Information Technology (IT) |
| Divisions: | Faculty of Information Technology (FIT) |
| Depositing User: | Hà Quang Thụy |
| Date Deposited: | 18 Jun 2021 11:17 |
| Last Modified: | 18 Jun 2021 11:17 |
| URI: | http://eprints.uet.vnu.edu.vn/eprints/id/eprint/4485 |
Actions (login required)
 |
View Item |
