Detecting Anomalous Behaviors Through User Journey Analytics

This chapter explores the use of user journey analytics to identify unusual actions by analyzing common user paths, with a focus on detecting anomalies like fraudulent activities in a bank setting. It discusses leveraging machine learning to automatically learn and categorize typical user journeys for anomaly detection. Additionally, the chapter emphasizes the importance of monitoring logs, collaborating between SOC and AppSec teams, and measuring metrics for successful security operations.