False positive detections are commonly caused by traffic match criteria in your
data patterns that are too generalized or may be instances where the
Enterprise DLP
machine learning (ML) models need to be manually trained.
Create specific and narrow
data pattern match criteria to add to
your
data profiles to help reduce the
likelihood of false positive detections. This can help you triage and more
easily implement changes when sensitive data isn't detected and blocked.