System and method for improving cybersecurity by generating activity reports using machine-learning models
US12155685B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 11, 2024 |
| Grant date | Nov 26, 2024 |
| Priority date | — |
| Expiry date | Jul 11, 2044 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L67/10
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Presented herein are systems and methods for generating suspicious activity reports using large language models. A system may include one or more processors that obtain event data associated with an event from a client device and from one or more databases, apply a prompt generator on the event data to generate a large language model (LLM) prompt, and generate a machine-readable suspicious activity (SAR) report in accordance with an LLM prompt. The one or more processors may also apply the prompt generator on the event data based on determining that a fraud risk score associated with the event satisfies a reporting threshold score. Computer program products are also presented.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.