X-FuseRLSTM: A Cross-Domain Explainable Intrusion Detection Framework in IoT Using the Attention-Guided Dual-Path Feature Fusion and Residual LSTM

X-FuseRLSTM: A Cross-Domain Explainable Intrusion Detection Framework in IoT Using the Attention-Guided Dual-Path Feature Fusion and Residual LSTM

Due to domain variability and developing attack tactics, intrusion detection in heterogeneous and dynamic IoT systems is still a crucial challenge. For cross-domain intrusion detection, this paper proposes a novel algorithm, X-FuseRLSTM, a dual-path feature fusion framework that is attention guided...

Full description

Saved in:
Bibliographic Details
Main Authors: Adel Alabbadi, Fuad Bajaber
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Sensors
Subjects:
neural networks
transformer
encoder
principal component analysis
attack
denial of service
Online Access:https://www.mdpi.com/1424-8220/25/12/3693
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1424-8220/25/12/3693

Similar Items