network-traffic-analysis

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

Real Intelligence Threat Analytics (RITA) is a framework for detecting command and control communication through network traffic analysis.

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

Materials about Encrypted Traffic Analysis

SaaS Zero - Network Traffic Monitor Professional network traffic monitoring and security analysis platform

A platform built for easy-to-use automated network traffic analysis

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.

The Attacker IP Prioritizer(AIP) dynamically generates resource-friendly IPv4 blocklists from Zeek network flows.

The model leverages the strengths of both CNNs and BiLSTM networks to effectively capture spatial and temporal patterns in network traffic data. We trained and evaluated the model using a comprehensive dataset of cyber attacks. The model achieved a high accuracy of 99%.

High-performance NetFlow, IPFIX and sFlow collector with flow analytics, ClickHouse storage, secure administration and cross-platform packages.

Notes for technologies useful in applying ml to the unsw-nb15 dataset (Draft)

Flonwix is a graphical network traffic analyzer for Linux-based systems that relies on ptcpdump

Keysight NAS (IXIA) Cloud Demo Examples

This repository provides comprehensive guides, configurations, rules, and practical examples for Snort, the open-source intrusion detection system (IDS). Ideal for cybersecurity professionals and enthusiasts looking to enhance their network security skills.

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

This project provides a clean, structured foundation for analyzing offline PCAP files.

Plug into extended SecOps: Bring Google Cloud's analytics to your local network. tshark captures on-prem, GCP transforms to UDM. Scalable, event-driven, via Terraform.