Using AI for Abnormal Behavior Detection

This is a presentation I used during my talk at the IT Summit Turkey 2019.

Transcript

1. Daron Yöndem http://daron.me @daronyondem
2. • Out of the Box Anomaly Detection for Cloud Apps • Anomaly Detection in the world of IoT • Anomaly Detector for Everyone
3. • Risky IP address • Login failures • Admin activity • Inactive accounts • Location • Impossible travel • Device and user agent • Activity rate
4. • Entity behavioral analytics (UEBA) • Machine learning (ML)
7. • Azure IoT Edge, Azure Stream Analytics offers built-in machine learning based anomaly detection • AnomalyDetection_SpikeAndDip and AnomalyDetection_ChangePoint
8. An AI service that helps you foresee problems before they occur
14. Microsoft Cloud App Security Product Page https://drn.fyi/375O6ML Anomaly Detection with Azure Stream Analytics and ML https://drn.fyi/33ZlpPu Online Playground for Anomaly Detector https://drn.fyi/2Qhqz5C Azure Anomaly Detector Video https://drn.fyi/2CHyl0z
15. http://daron.me | @daronyondem Download slides here; http://decks.daron.me