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Related Experiment Video

Updated: Sep 5, 2025

Evaluating Flight Performance and Eye Movement Patterns Using Virtual Reality Flight Simulator

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Published on: May 19, 2023

Simulation Training Auxiliary Model Based on Neural Network and Virtual Reality Technology.

¹Guangzhou Panyu Polytechnic, Guangzhou 511400, China.

Computational Intelligence and Neuroscience

|July 11, 2022

Summary

This summary is machine-generated.

This study introduces a novel Virtual Reality (VR)-based intrusion detection (ID) simulation training system. The proposed system utilizes a Convolutional Neural Network (CNN) and Long Short-term Memory (LSTM) model, significantly enhancing network security training effectiveness.

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Area of Science:

Computer Science
Cybersecurity
Virtual Reality

Background:

Training simulators are increasingly software-based, virtualized, and networked.
Network intrusion poses significant threats to computer and network security.
Virtual Reality (VR) technologies are maturing, offering new simulation possibilities.

Purpose of the Study:

To propose a VR-based intrusion detection (ID) simulation training system.
To develop an improved ID model for enhanced network security training.
To address challenges with unbalanced datasets in ID systems.

Main Methods:

Developed a VR-based simulation training system.
Proposed an ID model using Convolutional Neural Networks (CNN) and Long Short-term Memory (LSTM).
Implemented data oversampling techniques for unbalanced datasets.
Utilized 3DSMAX for process visualization and equipment modeling.

Main Results:

The CNN-LSTM model demonstrated superior performance compared to traditional methods like BP and GA.
The F1 index, a key evaluation metric, showed significant improvement, especially for D4.
CNN-LSTM outperformed GA by 12.75% and BP by 14.07% in performance.

Conclusions:

The VR-based ID simulation training system effectively meets its training objectives.
The developed CNN-LSTM model significantly enhances intrusion detection capabilities.
The simulation training approach proves impressive and effective for cybersecurity education.