Cyber anomaly detection using an artificial neural network
US11308393B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Jul 26, 2018 |
| Grant date | Apr 19, 2022 |
| Priority date | — |
| Expiry date | Oct 28, 2040 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/1425
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A hardware-based artificial neural network receives data patterns from a source. The hardware-based artificial neural network is trained using the data patterns such that it learns normal data patterns. A new data pattern is identified when the data pattern deviates from the normal data patterns. The hardware-based artificial neural network is then trained using the new data pattern such that the hardware-based artificial neural network learns the new data pattern by altering one or more synaptic weights associated with the new data pattern. The rate at which the hardware-based artificial neural network alters the one or more synaptic weights is monitored, wherein a training rate that is greater than a threshold indicates that the new data pattern is malicious.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.