IoT device identification by machine learning with time series behavioral and statistical features
US12301600B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 18, 2022 |
| Grant date | May 13, 2025 |
| Priority date | — |
| Expiry date | May 15, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Identifying Internet of Things (IoT) devices with packet flow behavior including by using machine learning models is disclosed. Information associated with a network communication of an IoT device is received. A determination of whether the IoT device has previously been classified is made. In response to determining that the IoT device has not previously been classified, a determination is made that a probability match for the IoT device against a behavior signature exceeds a threshold. The behavior signature includes at least one time series feature for an application used by the IoT device. Based at least in part on the probability match, a classification of the IoT device is provided to a security appliance configured to apply a policy to the IoT device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.