Volatility-based classifier for security solutions
US9485263B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 16, 2014 |
| Grant date | Nov 1, 2016 |
| Priority date | — |
| Expiry date | Jul 16, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2221/034
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Various embodiments provide an approach to classifying security events based on the concept of behavior change detection or “volatility.” Behavior change detection is utilized, in place of a pre-defined patterns approach, to look at a system's behavior and detect any variances from what would otherwise be normal operating behavior. In operation, machine learning techniques are utilized as an event classification mechanism which facilitates implementation scalability. The machine learning techniques are iterative and continue to learn over time. Operational scalability issues are addressed by using the computed volatility of the events in a time series as input for a classifier. During a learning process (i.e., the machine learning process), the system identifies relevant features that are affected by security incidents. When in operation, the system evaluates those features in real-time and provides a probability that an incident is about to occur.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.