A security team wants to detect unusual patterns in network traffic logs to flag potential intrusions. The dataset contains millions of unlabeled records with numeric features such as packet count, byte volume, and connection duration. The team has no labeled examples of attacks and needs a scalable SageMaker built-in algorithm that can identify statistical outliers in this high-dimensional data. Which algorithm best fits this requirement?