Machine Learning-Based Intrusion Detection Systems for the Internet of Drones: A Systematic Literature Review
The Internet of Drones (IoD) is a dynamic network architecture in which multiple drones, equipped with communication, sensing, and computation capabilities, are interconnected through Internet of Things (IoT) technologies to perform coordinated tasks autonomously. This infrastructure enables seamles...
Saved in:
| Main Authors: | Mostafa Ogab, Sofiane Zaidi, Abdelhabib Bourouis, Carlos T. Calafate |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11018757/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
BCAST IDS: A Novel Network Intrusion Detection System for Broadcast Networks
by: Javier Gombao
Published: (2025-01-01) -
Task Offloading Optimization Using PSO in Fog Computing for the Internet of Drones
by: Sofiane Zaidi, et al.
Published: (2024-12-01) -
Machine learning based intrusion detection framework for detecting security attacks in internet of things
by: V. Kantharaju, et al.
Published: (2024-12-01) -
Can Machine Learning Enhance Intrusion Detection to Safeguard Smart City Networks from Multi-Step Cyberattacks?
by: Jowaria Khan, et al.
Published: (2025-01-01) -
Forensic Examination of Drones: A Comprehensive Study of Frameworks, Challenges, and Machine Learning Applications
by: Elhaam Abdulrahman Debas, et al.
Published: (2024-01-01)