Patent ID: 11928857
Assignee: VMWARE LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method comprising:
receiving, by a computer system, an unlabeled training data set comprising a plurality of unlabeled data instances, each unlabeled data instance including values for a plurality of features;
for each feature in the plurality of features, training, by the computer system, a supervised machine learning (ML) model using a labeled training data set derived from the unlabeled training data set, wherein the labeled training data set comprises a plurality of labeled data instances, and wherein each labeled data instance includes:
a label corresponding to a value for the feature in an unlabeled data instance of the unlabeled training data set; and
values for other features in the unlabeled data instance;

receiving, by the computer system, a query data instance;
generating, by the computer system, a self-prediction vector using at least a portion of the trained supervised ML models and the query data instance, the self-prediction vector including values for the plurality of features that the query data instance should have if the query data instance is normal rather than anomalous; and
generating, by the computer system, an anomaly score for the query data instance based on the self-prediction vector and the query data instance.