Monitoring network activity for anomalies using activity metric forecasting model
US12068924B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 16, 2023 |
| Grant date | Aug 20, 2024 |
| Priority date | — |
| Expiry date | May 16, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L41/22
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Systems and methods are disclosed to implement a time series anomaly detection system that uses configurable statistical control rules (SCRs) and a forecasting system to detect anomalies in a time series data (e.g. fluctuating values of a network activity metric). In embodiments, the system forecasts future values of the time series data along with a confidence interval based on seasonality characteristics of the data. The time series data is monitored for anomalies by comparing actual observed values in the time series with the predicted values and confidence intervals, according to the SCRs. The SCRs may be defined and tuned via a configuration interface that allows users to visually see how different SCRs perform over real data. Advantageously, the disclosed system allows users to create custom anomaly detection triggers for different types of time series data, without use of a monolithic detection model which can be difficult to tune.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.