Patent · US Active

Variational autoencoding for anomaly detection

US11556855B2 · kind B2 · utility

0Cited by

2References

18Claims

0Family size

Assignee

SAP SE · DE

Inventors

Rajendra Kumar · Akron, US
Rahul Choudhary · Samastipur, IN
Seshadri Chatterjee · Sherghati, IN

Key dates

Filing date	May 22, 2020
Grant date	Jan 17, 2023
Priority date	—
Expiry date	Jul 17, 2041

Classification

Technology area (CPC G)Physics
CPC primaryG06N3/082
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A machine learning model including an autoencoder may be trained based on training data that includes sequences of non-anomalous performance metrics from an information technology system but excludes sequences of anomalous performance metrics. The trained machine learning model may process a sequence of performance metrics from the information technology system by generating an encoded representation of the sequence of performance metrics and generating, based on the encoded representation, a reconstruction of the sequence of performance metrics. An occurrence of the anomaly at the information technology system may be detected based on a reconstruction error present in reconstruction of the sequence of performance metrics. Related systems, methods, and articles of manufacture are provided.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.