Tasmanian devil optimization with deep autoencoder for intrusion detection in IoT assisted unmanned aerial vehicle networks

Tasmanian devil optimization with deep autoencoder for intrusion detection in IoT assisted unmanned aerial vehicle networks

Background: Recently, a developing count of physical objects is linked to the Internet at an unprecedented rate, calcifying the knowledge of the Internet of Things (IoT). In several paradigms of IoT applications, unmanned aerial vehicles (UAVs) and satellites for IoT have concerned much attention an...

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Bibliographic Details
Main Authors: Noha Negm, Hayam Alamro, Randa Allafi, Majdi Khalid, Amal M. Nouri, Radwa Marzouk, Aladdin Yahya Othman, Noura Abdelaziz Ahmed
Format: Article
Language:English
Published: Elsevier 2024-11-01
Series:Ain Shams Engineering Journal
Subjects:
Internet of things
Unmanned aerial vehicles
Deep autoencoder
Intrusion detection
Feature selection
Online Access:http://www.sciencedirect.com/science/article/pii/S2090447924003186
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