Isolation forest is the first anomaly detection algorithm that identifies anomalies using isolation, it was initially proposed and developed by Fei Tony Liu, Kai Ming Ting and Zhi-Hua Zhou in 2008. The significance of this research lies in its deviation from the mainstream philosophy underlying existing anomaly detectors at the time, where normal instances are profiled before anomalies are identified as instances that do not conform. Isolation forest introduces a fundamentally different method that explicitly isolates anomalies using binary trees, demonstrating the new possibility of a fast anomaly detector that directly targets anomalies without the resource intensive process of normal instance profiling. The algorithm has a linear time complexity with a low constant and a low memory requ