PROJECT FILE / CASE STUDY

R-M UEBA AI Engine

A continuous authentication exploration using keystroke timing and behavioral analytics.

AI
VISUAL CONCEPT • NOT A SYSTEM SCREENSHOT
AI / PROJECT FILE
DisciplineArtificial intelligence
Evidence statusDocumented in the README; not independently operationally verified.
AttributionA team member portfolio project; inclusion does not imply a MADAR commercial engagement.
01 / CONTEXT

Challenge & context

Studying behavioral drift during a session while acknowledging the sensitivity of behavioral data.

02 / APPROACH

Solution approach

The repository documents a Random Forest model and SIEM signals. Unverified accuracy figures are not repeated.

03 / DOCUMENTED CAPABILITIES

What the available evidence supports

  • Dwell-time and inter-key timing features
  • A monitoring dashboard and JSON signals
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