Next-Gen Cyber Threat Detection Powered by Artificial Inteligence
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Stay one step ahead of hackers with real-time AI-powered threat detection designed for encrypted environments.
Next-Gen Cyber Threat Detection Powered by Artificial Inteligence
|
Stay one step ahead of hackers with real-time AI-powered threat detection designed for encrypted environments.
Key Features
Real-time Prediction
Instantly detect cyber threats from your network data using advanced AI models.
High Accuracy
Our Hybrid model achieves 98.15% test accuracy ensuring reliable threat detection.
Visual Reports
Get results in color-coded tables and pie charts for easy analysis.
Download Results
Download your prediction results in CSV or PDF format for record keeping.
Try Our Live Demo
Upload your network CSV file and get instant AI-powered predictions for cyber threats. See which activities are safe and which may be malicious, all in a simple, easy-to-read format.
Model Accuracy & Performance
Check out how our AI models perform in detecting cyber threats using the CICIDS 2017 dataset.
| Model | Accuracy | Precision | Recall | F1-Score |
|---|---|---|---|---|
| Hybrid Model | 98.15% | 0.98 | 0.98 | 0.98 |
Dataset: CICIDS 2017
Hybrid Model
Accuracy: 98.15%
About CyberGuard
Check out how our AI models perform in detecting cyber threats using the CICIDS 2017 dataset.
CyberGuard is an AI-powered system designed to detect cyber threats in network traffic. Using advanced deep learning and machine learning models, including ERNN, CNN, LSTM, GRU, and XGBoost, it identifies malicious activity with high accuracy. Our hybrid model approach ensures reliable predictions while providing visual reports and downloadable results for easy analysis.
How it Works
Explanations
CyberGuard is an AI-powered cyber threat detection system designed to identify malicious activities in network traffic with high precision. By combining advanced deep learning models such as ERNN, CNN, LSTM, and GRU with powerful machine learning classifiers like XGBoost, CyberGuard ensures accurate detection of attacks while minimizing false alarms.
Our hybrid approach leverages a Deep Stacked Autoencoder to extract complex traffic patterns, feeding them into XGBoost for precise classification. Users can easily upload network CSV files, visualize results in intuitive tables and charts, and download detailed reports for further analysis. CyberGuard provides a reliable, fast, and user-friendly solution for securing network environments.