Enhancing IoT Security Using GA-HDLAD: A Hybrid Deep Learning Approach for Anomaly Detection

Enhancing IoT Security Using GA-HDLAD: A Hybrid Deep Learning Approach for Anomaly Detection

The adoption and use of the Internet of Things (IoT) have increased rapidly over recent years, and cyber threats in IoT devices have also become more common. Thus, the development of a system that can effectively identify malicious attacks and reduce security threats in IoT devices has become a topi...

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Bibliographic Details
Main Author: Ibrahim Mutambik
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Applied Sciences
Subjects:
Internet of Things (IoT)
IoT security
anomaly detection
hybrid deep learning (HDL)
genetic algorithm (GA)
feature extraction techniques (FETs)
Online Access:https://www.mdpi.com/2076-3417/14/21/9848
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