Introduction

An Intrusion Detection System (IDS) gathers data from various sources to detect threats and malicious behavior. These sources are mainly divided into host-based and network-based information sources.

Host-Based Information Sources

Host-based sources collect data from individual systems such as servers and workstations. They help detect internal threats by providing detailed insights into local activities.

• System Logs: Operating system and application logs that record unusual activities.

• File Integrity Checking: Monitors changes to files and directories.

• Process Monitoring: Tracks running processes and resource usage.

• Audit Trails: Records user activities and system events.

Network-Based Information Sources

Network-based sources monitor traffic across the network to detect external threats. They provide a broad view of the overall network activity.

• Network Traffic Logs: Capture packets of data traveling through the network (e.g., Wireshark, tcpdump).

• Firewall Logs: Record information about incoming and outgoing traffic, including blocked attempts.

• Router/Switch Logs: Document routing protocols and data flow within the network.

• NIDS/NIPS Logs: Logs from dedicated network intrusion detection/prevention systems (e.g., Snort, Suricata).

Combining Information Sources

Using both host-based and network-based sources gives a complete view of security events. This approach enhances threat detection by capturing details from different perspectives, allowing real-time and system-wide monitoring.

For example, an attack might bypass network defenses but leave traces in host logs, such as file modifications or unauthorized access.

Goals of Intrusion Detection Systems (IDS)

IDS are designed with several key goals in mind:

• Attack Detection: Identify malicious activities, unauthorized access, or policy violations.

• Alerting and Notification: Inform administrators or security teams when threats are detected.

• Analysis and Forensics: Provide logs and data that help in investigating security breaches.

• Prevention: When integrated with Intrusion Prevention Systems (IPS), help block attacks automatically.

• Policy Enforcement: Ensure compliance with security policies and optimize resource usage.

Architecture of IDS

The IDS architecture outlines the components and data flows used to collect, analyze, and respond to threats.

Key Components

• Sensors (Data Collection): Gather data from host-based and network-based sources.

• Detection Engine: Analyzes the collected data using signature-based or anomaly-based methods.

• Alerting System: Notifies administrators of detected threats through email, SMS, or SIEM integration.

• Response System: Takes actions such as logging events or blocking malicious activity.

Data Collection and Analysis

• Data Collection Layer: Sensors gather logs, network traffic, and other system data.

• Detection Techniques: The engine uses known signatures and behavioral analysis to identify threats.

IDS Design Considerations

When designing and deploying an IDS, several factors should be taken into account to ensure effectiveness:

• Scalability: The system must handle large volumes of data and high traffic rates.

• Accuracy: It should minimize false positives and negatives.

• Deployment Flexibility: Choose between host-based, network-based, or hybrid IDS based on the environment.

• Integration: Seamlessly work with other security tools like firewalls and SIEM systems.