Using Machine Learning for Behavior-Based Access Control: Scalable Anomaly Detection on TCP Connections and HTTP Requests

This paper focuses on the statistical machine learning techniques used in BBAC to make predictions about the intent of actors establishing TCP connections and issuing HTTP requests and discusses pragmatic challenges and solutions encountered in implementing and evaluating BBAC.