Detection pipeline
Captured packet information is converted into model-ready features and passed to a trained Random Forest classifier. Normal traffic is recorded and released, while suspicious classifications enter the response path.
All projectsCybersecurity · Machine Learning
Neuro-Shield
An AI-assisted intrusion-detection framework that classifies network activity and connects detection to alerts and rule-based defensive actions.
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System architecture
Self-healing response
The response module maps classified attack types to transparent operating-system actions. This rule-based design keeps intervention understandable and testable while demonstrating how detection can connect to mitigation.
Human visibility
A Telegram bot reports attack information so that automated action does not become invisible action. The project treats timely notification and recorded evidence as part of the security workflow.