Ensemble learning-based intrusion detection
| dc.contributor.author | Lies, Ziar | |
| dc.contributor.author | Katiba, Halimi | |
| dc.contributor.author | Bourouis, Abdelhabib | |
| dc.date.accessioned | 2024-10-17T20:17:47Z | |
| dc.date.available | 2024-10-17T20:17:47Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | In the context of the rapid evolution of drone technologies, the Internet of Drones (IoD) plays a crucial role in various applications, ranging from surveillance to package delivery. However, with the increased use of drones, the security of drone systems has become a major concern. This project aims to develop an ensemble learning-based intrusion detection system (IDS) to enhance the security of drone networks. The results obtained during this study demonstrate that the application of ensemble learning in the field of intrusion detection for drone systems is promising. This model provides an effective and robust solution to improve drone network security, addressing a growing issue in the Internet of Drones field. | |
| dc.identifier.uri | http://dspace.univ-oeb.dz:4000/handle/123456789/20056 | |
| dc.language.iso | en | |
| dc.publisher | University of Oum El Bouaghi | |
| dc.title | Ensemble learning-based intrusion detection | |
| dc.title.alternative | System for Internet of Drones (IoDs) | |
| dc.type | Other |
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