Anomaly detection in time series data

Abstract

Described herein are systems, mediums, and methods for detecting blockage of network traffic at a network server. A signal representative of time series data associated with network traffic is received at a processor for analysis. A data segmentation algorithm and an anomaly detection algorithm are applied in series to the received data. The segmentation algorithm detects regime shifts in the data. Data between regime shifts is considered a segment of data. The anomaly detection algorithm analyzes each segment individually to determine whether anomalies exist in the segment. If a cyclic pattern is found in the segment, the cyclic pattern is extracted from the segment leaving a residual data for analysis. A probability distribution of the residual data is determined for analysis. When an anomaly is detected in the segment o based on the probability distribution of the residual data, it is determined that blockage has occurred on the network traffic.