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DLP Accuracy Demonstrations

Accurate DLP rules are critical to an effective DLP solution.

False positives (mistakenly detecting something) interfere with productivity.
End-users and information workers may be blocked from completing their task.
Administrators will receive additional support requests, requiring deep content investigations.

False negatives (not detecting something) allow sensitive information and company data assets to be leaked, putting your employees and company at risk.

Below are some demonstrations of the accuracy for a few of Nucleuz's DLP rules.

  IPv4 Address

Demonstration of Nucleuz's IPv4 Address rule accuracy, including false positive and false negative scenarios.

  IPv6 Address

Accuracy demonstration of Nucleuz's IPv6 Address rule which covers some examples of detecting IPv6 addresses, including several false negative.

  Australian Tax File Number

Get a glimpse of the accuracy of detecting Australian Tax File Numbers with Nucleuz's Premium DLP rules.

This demo covers examples of detecting Australian Tax File Numbers, including several false positive and negative examples.