Applying Machine Learning to Detect DDoS Attacks in SD-VANET Networks
Applying Machine Learning to Detect DDoS Attacks in SD-VANET Networks
Keywords:
Vehicular Ad Hoc Network, Software Defined Networks. Distributed denial of service attackAbstract
Vehicular Ad Hoc Network (VANET) is a modern technology that integrates next-generation wireless network capabilities into vehicles. Integrating Software-Defined Networking (SDN) with VANETs is a significant step towards developing intelligent vehicular networks. This new architecture offers innovative solutions to VANET challenges in various fields, especially in security.Using machine learning to detect Distributed Denial of Service (DDoS) attacks in Software-Defined VANETs (SD-VANET) is a modern and effective technique. This approach relies on analyzing network traffic patterns and detecting abnormal behaviors that indicate DDoS attacks. Machine learning algorithms can quickly and accurately identify these patterns, helping to take preventive measures to protect the network.
In this research, an SDN-VANET environment was created using the Mininet-WiFi emulator, with the Ryu controller providing software components and APIs that facilitate developers in creating new applications for network management and control. Statistical information extracted from flow tables was used to detect DDoS attacks targeting controllers in the SDN-VANET environment. The dataset used to train the machine learning model was obtained from the experimentally designed SD-VANET architecture, and the best-performing parameters for the SVM classifier were used during the training phase, resulting in high accuracy.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-sa/4.0/
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The authors retain the copyright and grant the right to publish in the magazine for the first time with the transfer of the commercial right to Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series
Under a CC BY- NC-SA 04 license that allows others to share the work with of the work's authorship and initial publication in this journal. Authors can use a copy of their articles in their scientific activity, and on their scientific websites, provided that the place of publication is indicted in Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series . The Readers have the right to send, print and subscribe to the initial version of the article, and the title of Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series Publisher
journal uses a CC BY-NC-SA license which mean
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material
- The licensor cannot revoke these freedoms as long as you follow the license terms.
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes.
- ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.