Abstract: iFores (isolation Forest) algorithm has a low detection ability for local outlier detection, and the
detection time of LOF (Local Outlier Factor) algorithm is longer, and a improved algorithm which can solve these
problems named iForest-WHT (isolation Forest based on Waterfall Hybrid Technology) is proposed. Based on the
idea of waterfall hybrid technology, the iForest algorithm is used as the filter, the split path is the threshold
judgment method, the data with path less than the threshold is put into the candidate anomaly subset. Then the
improved LOF algorithm considering the extreme value is used to refine the candidate anomaly subset to obtain
more accurate anomaly subset. The experimental results show that the algorithm can identify the outliers at higher
efficiency, improve the F 1 value of the algorithm and reduce the false alarm rate of the original LOF algorithm.

Key words: waterfall hybrid technology, local outlier factor, anomaly detection, isolation forest