What does behavioral-based detection rely on to identify malicious activity?

Behavioral-based detection is a security approach that identifies malicious activity by analyzing the patterns of behavior exhibited by users and systems rather than relying on signatures of known threats. This method focuses on how entities act and the anomalies in their behavior that could indicate potential security incidents.

For instance, if an application typically accesses a certain set of files and suddenly attempts to access a large number of files in a very short time frame, this unusual behavior can trigger alerts. Such detection is particularly effective against novel or previously unknown threats that may not yet have established signatures in a database.

While real-time monitoring tools are commonly used in conjunction with behavioral-based detection systems to analyze and alert on actions, the core concept relies on behavioral patterns instead of pre-defined signatures. Additionally, detecting threats based on physical location or conventional signature-based methodologies does not capture the dynamic nature of anomalous activities that this detection method excels at addressing.