Azure Ad Fraud Detection - Azure AFD Caching

Detecting Anomalies in Azure Ad Authentication

This section explores advanced techniques for identifying fraudulent activity within Azure Ad, aiming to mitigate potential security risks.

We're focusing on patterns beyond simple log analysis...

Key Metrics & Algorithms

We use machine learning to identify:

• Behavioral Anomalies: Detecting deviations from established user behaviors (e.g., atypical login times, location patterns).
• Log Correlation: Analyzing logs across multiple sources for contextual insights.
• Rule-Based Detection: Predefined rules to flag suspicious activity.
• Anomaly Scoring: Assigning a risk score to potential anomalies.