Data Classification & Sensitive Information TypesDetection Logic Deep Dive

Detection Logic Deep Dive

35 mins

Understanding the Concept

Understanding detection logic is crucial for tuning policies and troubleshooting false positives/negatives. DLP detection combines multiple signals: SIT matches, content location, sender/recipient, file properties, and more.

Confidence levels (Low: 65%, Medium: 75%, High: 85%) are calculated based on how many supporting elements are present. A credit card number alone might be low confidence, but with expiry date and CVV keywords, it becomes high confidence.

Instance counts matter too: detecting 1-9 instances might trigger a warning, while 10+ instances triggers blocking. This helps distinguish between incidental mentions and actual data exfiltration.

Key Points

  • Primary Element: The core pattern being matched
  • Supporting Elements: Keywords, additional patterns within proximity
  • Confidence Levels: Low (65%), Medium (75%), High (85%)
  • Instance Count: How many matches trigger which action
  • Proximity: Character distance for supporting elements

Detection Logic Flow

Step 1

Content Scan

Document/email/message is scanned for patterns

Step 2

Pattern Match

Primary patterns are identified (regex, checksums)

Step 3

Context Analysis

Supporting keywords checked within proximity

Step 4

Confidence Calculation

Score calculated based on elements present

Step 5

Threshold Check

Instance count compared to policy thresholds

Step 6

Action Trigger

Appropriate action taken based on match

Why This Matters in Real Organizations

Misconfigured detection logic leads to either missed detections (risk) or excessive false positives (user frustration and policy fatigue). Understanding these mechanics lets you fine-tune policies for optimal balance.

Common Mistakes to Avoid

Using low confidence when high is needed
Setting instance counts too low for normal business use
Not understanding proximity implications
Ignoring the 'unique' vs 'any' instance count option

Interview Tips

  • Explain confidence levels and how to choose
  • Describe a troubleshooting scenario for false positives
  • Discuss tuning strategies

Exam Tips (SC-401)

  • Know the default confidence percentages
  • Understand instance count configurations
  • Know how proximity affects detection

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