Patent ID: 11916948
Assignee: SENSEON TECH LTD
Field: Digital communication (Electrical engineering)
Classification: CPC H  G | IPC H

Claim 0:
1. A computer-implemented method of detecting potential cybersecurity threats from a cybersecurity dataset, the method comprising:
structuring the cybersecurity dataset as a first data matrix, each row of the first data matrix being a datapoint and each column corresponding to a feature;
applying an unsupervised classification process to the first data matrix to classify each datapoint in relation to a set of classes;
based on the unsupervised classification process, re-structuring the cybersecurity dataset as a second data matrix; and
applying anomaly detection to the second data matrix, the anomaly detection incorporating class information obtained in the unsupervised classification process, wherein the anomaly detection comprises identifying a datapoint of the second data matrix as anomalous using a residuals matrix, the residuals matrix computed between the second data matrix and an approximation of the second data matrix, by applying a truncated singular value decomposition (SVD) to the second data matrix,, wherein the datapoint is identified as anomalous based on:
a row of the residuals matrix corresponding to the datapoint, or
a second-pass coordinate vector of the datapoint, as determined by applying a applying a second-pass SVD to the residuals matrix.