Energy-efficient deep learning-based intrusion detection system for edge computing: a novel DNN-KDQ model

Energy-efficient deep learning-based intrusion detection system for edge computing: a novel DNN-KDQ model

Abstract The proliferation of the Internet of Things (IoT) and edge computing technologies has expanded the attack surface for cybercriminals, emphasizing the need for robust and efficient cybersecurity measures. Intrusion detection systems (IDS) are essential defenses; however, deploying traditiona...

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Bibliographic Details
Main Authors: Hafiz Gulfam Ahmad Umar, Iqra Yasmeen, Muhammad Aoun, Tehseen Mazhar, Muhammad Amir Khan, Ines Hilali Jaghdam, Habib Hamam
Format: Article
Language:English
Published: SpringerOpen 2025-07-01
Series:Journal of Cloud Computing: Advances, Systems and Applications
Subjects:
DNN-KDQ model
Intrusion detection system (IDS)
Deep learning models
Energy efficiency
Cybersecurity
Edge computing
Online Access:https://doi.org/10.1186/s13677-025-00762-9
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https://doi.org/10.1186/s13677-025-00762-9

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