Malcolm is a powerful, easily deployable network traffic analysis tool suite for full packet capture artifacts (PCAP files), Zeek logs and Suricata alerts.

Malcolm is a powerful, easily deployable network traffic analysis tool suite for full packet capture artifacts (PCAP files), Zeek logs and Suricata alerts.

A Python-based network traffic analyzer for PCAP files, providing insights into protocol distribution, IP communications, and potential port scanning activities.

Malcolm is a powerful, easily deployable network traffic analysis tool suite for full packet capture artifacts (PCAP files), Zeek logs and Suricata alerts.

This project is a live network monitoring dashboard that leverages tree-based machine learning algorithms to detect intrusions in real-time. The system uses Flask and Socket.IO for real-time data updates, and Chart.js for data visualization. The dashboard provides various charts to visualize network data and sends notifications for suspicious activ

Dryad: Deploying Adaptive Trees on Programmable Switches for Networking Classification (ICNP2023)

Major project for Advanced Topics in Computer Science. Using mitmproxy to automatically detect if private data has been leaked in network traffic data by certain android applications.

Kali Linux sanal makinesi kullanarak DDoS saldırılarının simülasyonunu gerçekleştirip, oluşturulan veri seti üzerinde makine öğrenme algoritmaları ile saldırı tespiti ve normal trafikten ayırma.

Network traffic analysis, traffic characteristics extraction, flow migration and evaluation