Identifying and protecting against an attack against an anomaly detector machine learning classifier
US11297083B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 15, 2019 |
| Grant date | Apr 5, 2022 |
| Priority date | — |
| Expiry date | Sep 30, 2040 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/1466
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Identifying and protecting against an attack against an anomaly detector machine learning classifier (ADMLC). In some embodiments, a method may include identifying training data points in a manifold space for an ADMLC, dividing the manifold space into multiple subspaces, merging each of the training data points into one of the multiple subspaces, training a subclassifier for each of the multiple subspaces to determine a decision boundary for each of the multiple subspaces between normal training data points and anomalous training data points, receiving an input data point into the ADMLC, determining whether the input data point is an attack on the ADMLC due to a threshold number of the subclassifiers classifying the input data point as an anomalous input data point, and, in response to identifying the attack against the ADMLC, protecting against the attack.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.