ThreatVision AI: A Machine Learning Approach to Network Threat Detection

ThreatVision AI ThreatVision AI is an AI-powered cybersecurity platform designed to identify potentially malicious network activity through machine learning and interactive data visualization. The project was developed as an educational cybersecurity application that demonstrates how artificial intelligence can assist in network-threat detection and security monitoring. The system analyzes network-log data and evaluates patterns associated with suspicious behavior, including failed login attempts, connection activity, packet characteristics, login times, and port-access patterns. Using machine-learning techniques, ThreatVision AI classifies network activity as either normal or potentially malicious and presents the results through an interactive dashboard. A Random Forest machine-learning model serves as the primary threat-classification engine, while additional models such as Decision Tree and Logistic Regression are used for comparison and evaluation. The platform provides threat statistics, risk-level indicators, security alerts, and visual analytics that help users understand network behavior and potential security concerns. The project was built using Python, Scikit-Learn, Pandas, Plotly, and Streamlit, allowing users to upload network-log datasets and receive real-time analysis through a browser-based interface. ThreatVision AI demonstrates the practical application of machine learning in cybersecurity and highlights how AI can support the early identification of suspicious network activity. Key Features Network-log CSV upload and processing Machine-learning-based threat detection Normal vs. suspicious activity classification Random Forest threat prediction model Interactive cybersecurity dashboard Threat statistics and security analytics Risk-level categorization and alerts Data visualization using Plotly Browser-based deployment with Streamlit Technology Stack Python Pandas NumPy Scikit-Learn Streamlit Plotly Joblib Project Impact ThreatVision AI demonstrates the integration of Artificial Intelligence and Cybersecurity by applying machine-learning techniques to network-threat detection. The project was developed as a portfolio and educational research project to explore how intelligent systems can assist security analysts in identifying suspicious behavior and improving cybersecurity awareness.