Host-Based Intrusion Protection (HIPS) systems are often deployed in monitoring or learning mode during their initial implementation. What is the objective of starting in this mode?

In learning/monitoring mode, HIPS passively observes system activity and automatically creates exceptions for actions and files it encounters, effectively building a whitelist of known-good behavior. This prevents the system from blocking legitimate operations once it transitions to enforcement mode. The auto-generated exceptions represent the primary output and objective of the learning phase.

Blacklisting unsafe files is a function of enforcement or protection mode, not monitoring/learning mode; learning mode is designed to identify and permit normal activity, not to flag or block suspicious files.

While learning mode does result in whitelisting, the mechanism described here - automatically whitelisting files 'already known to the system' - describes a static signature or reputation-based approach, not the dynamic baseline-building process that monitoring mode performs.

Building a baseline of normal system events is more characteristic of anomaly-based IDS/IPS or behavioral analytics tools; HIPS learning mode specifically focuses on generating exception rules (whitelists) from observed activity rather than simply recording a passive baseline for human review.