Systems and methods for configuring and implementing a card testing machine learning model in a machine learning-based digital threat mitigation platform
US11429974B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 19, 2021 |
| Grant date | Aug 30, 2022 |
| Priority date | — |
| Expiry date | Jul 19, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/1466
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Systems and methods for detecting digital abuse or digital fraud that involves malicious account testing includes implementing a machine learning threat model that predicts malicious account testing using misappropriate accounts, wherein a subset of a plurality of learnable variables of an algorithmic structure of the machine learning threat model includes one or more learnable variables derived based on feature data indicative of malicious account testing; wherein implementing the machine learning threat model includes: (i) identifying event data from an online event that is suspected to involve digital fraud or digital abuse, (ii) extracting adverse feature data from the event data that map to the one or more learnable variables of the subset, and (iii) providing the adverse feature data as model input to the machine learning threat model; and computing, using the machine learning threat model, a threat prediction indicating a probability that the online event involves malicious account testing.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.