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January 1, 2026INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTSOpen Access

Dual-Stage Data Fusion and Hybrid Deep Learning Framework for Robust Intrusion Detection in Network Traffic

Ram Naresh Sharma Jitendra Singh Kushwah Pritaj Yadav

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Key Points

The research aims to enhance intrusion detection in network traffic through a dual-stage data fusion and hybrid deep learning model.
Developed a hybrid deep learning framework combining various algorithms.
Implemented a dual-stage data fusion approach to improve detection accuracy.
Analyzed network traffic data for training and testing the model.
The model significantly improved accuracy in identifying intrusions compared to traditional methods.
Demonstrated robustness against various types of network attacks.

Implication

Demonstrates robust intrusion detection in network traffic using a hybrid deep learning framework, indicating improved security measures.

Abstract

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Cite This Study

Sharma et al. (2026) studied this question.

synapsesocial.com/papers/69c7723a8bbfbc51511e29c7 https://doi.org/10.56975/ijcrt.v14i3.303582

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