Patent ID: 11275639

Abstract:
The present disclosure provides systems and methods for detecting and correlating anomalous time-series data. A system may receive and process time-series data associated with one or more network data streams to generate sets of aligned time-series data. The system may detect anomalous time-stamped data points in the sets of aligned time series data and generate groups of annotated time-series data. The annotation identifies specific time-stamped data points as anomalous. The system may determine the number of anomalous groups of annotated time-series data within all groups of annotated time-series data and may further determine the probability that one or more anomalous groups belong to at least one of the groups of annotated time-series data using a generative statistical model and outputting one or more correlated anomalous groups. The system may generate a detailed statistical report for each correlated anomalous group and output an aggregated statistical report for the correlated groups.