🛡️ CIC-UNSW Dataset Analysis

Comprehensive Network Traffic Analysis for Intrusion Detection

📊 Total Records

447,915
Network Flow Records

🔢 Features

76
Flow-Based Features

🎯 Attack Types

5
Different Attack Categories

✅ Data Quality

99.8%
Completeness Rate

📈 Attack Distribution Analysis

Understanding the threat landscape in network traffic

Attack Type Distribution

Traffic Classification

💡 Key Insights & Recommendations

Strategic insights for cybersecurity implementation

🎯 Primary Threats

Analysis and Exploits represent the most significant threats in the dataset, requiring immediate attention in your security infrastructure.

📊 Data Quality

Excellent data completeness (99.8%) ensures reliable machine learning model training and accurate threat detection capabilities.

🔍 Feature Rich

76 flow-based features provide comprehensive network behavior analysis, enabling sophisticated intrusion detection systems.

⚡ Real-time Ready

Flow-based features are ideal for real-time monitoring and can be implemented in production network security systems.

🤖 ML Ready

Large dataset size (447K+ records) provides sufficient data for training robust machine learning models for threat detection.

🛡️ Multi-class Detection

Support for 5 different attack types enables comprehensive security coverage across various threat vectors.