Methods used to detect unauthorized access or anomalies in computer systems and networks.
Description
Intrusion Detection Techniques are crucial components of cybersecurity that focus on identifying potential threats and unauthorized access attempts to computer systems and networks. These techniques can be broadly categorized into two main types: network-based intrusion detection systems (NIDS) and host-based intrusion detection systems (HIDS). NIDS monitor network traffic for suspicious activities, while HIDS analyze events on individual devices for signs of intrusion. Some commonly used methodologies include signature-based detection, which relies on predefined patterns of known threats, and anomaly-based detection, which establishes a baseline of normal behavior and flags deviations from that norm. Effective intrusion detection not only helps in identifying breaches but also plays a significant role in compliance with security standards such as GDPR and PCI DSS. As cyber threats continue to evolve, utilizing advanced technologies like machine learning in conjunction with traditional methods is becoming increasingly important for organizations seeking to protect sensitive data and maintain their reputations.
Examples
- Snort: An open-source network intrusion detection system that analyzes network traffic in real-time.
- OSSEC: A host-based intrusion detection system that monitors server and endpoint activities for malicious behavior.
Additional Information
- Intrusion detection systems can generate alerts, but they do not typically prevent attacks; they are often paired with intrusion prevention systems (IPS).
- Regular updates and tuning of detection rules are essential to adapt to new threats and reduce false positives.