Why is anomaly detection considered a behavior-based method?

Anomaly detection is considered a behavior-based method primarily because it focuses on identifying deviations from established patterns of normal behavior within a system or network. This methodology hinges on understanding what constitutes 'normal' activity for users, processes, or systems and then monitoring for any irregularities that fall outside of these expected behaviors. By assessing deviations from these baseline activities, anomaly detection can effectively identify potential security threats or incidents that may not be captured by traditional signature-based detection methods, which rely on pre-identified threat signatures.

This approach is beneficial in that it can uncover zero-day attacks or previously unknown threats, as it doesn't limit its scope to only identifying known security risks. Instead, it seeks to identify any activity that significantly differs from normal operations, which is critical in environments where threats are constantly evolving. By focusing on behavior rather than specific signatures, anomaly detection empowers organizations to respond to potential threats that may not yet have defined signatures in existing security databases.