Deep Transfer Learning Based on Hybrid Swin Transformers With LSTM for Intrusion Detection Systems in IoT Environment

Deep Transfer Learning Based on Hybrid Swin Transformers With LSTM for Intrusion Detection Systems in IoT Environment

Extensive growth in the number of Internet Of Things (IoT) devices has significantly increased susceptibility to various cyber-attacks and hence emphasized the need for robust intrusion detection systems (IDS) for ensuring IoT network security. While deep learning (DL) methodologies have proven effe...

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Bibliographic Details
Main Authors: Ibrahim A. Fares, Ahmed Gamal Abdellatif Ibrahim, Mohamed Abd Elaziz, Mansour Shrahili, Adham Ahmed Elmahallawy, Rana Muhammad Sohaib, Mahmoud A. Shawky, Syed Tariq Shah
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Open Journal of the Communications Society
Subjects:
Cyber-security
intrusion detection system (IDS)
IoT
transformers
transfer learning
Online Access:https://ieeexplore.ieee.org/document/11005405/
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