Anomaly detection is indispensable in security to detect threats early or identify unusual behavior. For anomaly detection, our Dynatrace Davis® AI provides different anomaly detection analyzers, which can be simulated in the notebook for better understanding.
In this Observability Lab hosted by Andi Grabner @andreas_grabner we begin with David Bründl who recaps when to apply the various anomaly detection strategies such as static, auto-adaptive and seasonal baselining.
We then hear from Gerhard Bryne @GerhardByrne on how Anomaly Detection applied to Security Use Cases makes security engineers more efficient when analyzing scenarios such as abnormal authentication requests.
Links discussed:
Notebook on Playground
Getting Started with Dynatrace:
🎥 Anomaly Detection on 5 Pillars of Data Observability with Dynatrace Davis AI
Davis Anomaly Detection app: https://dynatr.ac/4bgQC2A
Chapter List:
00:00 - Introduction
01:05 - Recap - Davis AI Analyzer
01:52 - Demo - How Davis AI Analyzer works
02:40 - Demo - Static Thresholds
05:03 - Demo - Auto-Adaptive Thresholds
10:20 - Demo - Seasonal Baseline
14:20 - Applying this to Security Use Cases
14:39 - Anomaly Detection for Security
17:24 - How Anomaly Detection fits into Incident Evaluation
19:03 - Use Case: Detecting Anomalous Authentication Errors
19:45 - Demo - Query Authentication Errors
20:50 - Demo - Create Anomaly Detection
23:33 - Demo - Authentication Alert Workflow
24:55 - Demo - Security Investigator
31:34 - More Security Use Cases
Recording on Dynatrace University.
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