Intrusion Detection Dataset

Intrusion Detection is a critical aspect of cybersecurity, aimed at identifying and preventing unauthorized access or malicious activities on a network. This dataset provides a comprehensive collection of network traffic data, labeled with various intrusion types.

Dataset Overview

• Data Source: Network traffic logs from various organizations
• Data Format: CSV
• Intrusion Types: 42 different types of intrusions, including DoS, probes, R2L, etc.
• Sample Size: Over 2.8 million records

Features

• TCP/IP Header Information: Source and destination IP addresses, ports, and protocols
• Packet Payload: Data payload of the network packets
• Timestamp: Time when the packet was captured

Usage

This dataset can be used for:

• Machine Learning Models: Training and evaluating intrusion detection models
• Data Science Projects: Analyzing network traffic patterns and identifying potential threats
• Educational Purposes: Learning about network security and intrusion detection techniques

Additional Resources

For more information on intrusion detection and related datasets, please visit our cybersecurity resources page.

Intrusion Detection System Architecture