Detecting Fraudulent User Flows

Mechanisms are provided for detecting fraudulent user flows associated with a website. User flow data, representing an interaction by a user with content of a website, is received and converted to a vector representation that represents a time series transition from one portion of website content to another of the website. The vector representation is input to a trained sequential machine learning computer model which generates a classification of the vector representation. A determination as to whether or not the user flow data represents a fraudulent user flow is made based on the classification. An output is generated that indicates whether or not the user flow is a fraudulent user flow based on the detection.