Applied Sciences, Free Full-Text
Por um escritor misterioso
Last updated 21 março 2025

The rapid growth of the Internet of Things (IoT) has led to an increased automation and interconnectivity of devices without requiring user intervention, thereby enhancing the quality of our lives. However, the security of IoT devices is a significant concern as they are vulnerable to cyber-attacks, which can cause severe damage if not detected and resolved in time. To address this challenge, this study proposes a novel approach using a combination of deep learning and three-level algorithms to detect attacks in IoT networks quickly and accurately. The Bot-IoT dataset is used to evaluate the proposed approach, and the results show significant improvements in detection performance compared to existing methods. The proposed approach can also be extended to enhance the security of other IoT applications, making it a promising contribution to the field of IoT security.

Applied Sciences An Open Access Journal from MDPI

Applied Energy, Journal

Applied Sciences An Open Access Journal from MDPI

Advanced Science - Wiley Online Library

Applied Sciences An Open Access Journal from MDPI

AHS Undeclared

Applied Sciences An Open Access Journal from MDPI

Applied Sciences An Open Access Journal from MDPI
Applied Sciences Inc. - Nanomaterials - Carbon Fibers - Nanomat
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Applied Sciences An Open Access Journal from MDPI

Applied Sciences An Open Access Journal from MDPI

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