System and methods for dynamic digital threat mitigation

US10296912B2 · kind B2 · utility

Assignee

• Sift Science, Inc. · US

Inventors

• Fred Sadaghiani · San Francisco, US
• Alex Paino · San Francisco, US
• Jacob Burnim · San Francisco, US
• Keren Gu · San Francisco, US
• Gary Lee · San Francisco, US
• Noah Grant · San Francisco, US
• Eugenia Ho · San Francisco, US
• Doug Beeferman · San Francisco, US

Key dates

• Filing date: Sep 21, 2018
• Grant date: May 21, 2019
• Expiry date: Sep 21, 2038

Classification

• Technology area (CPC H): Electricity
• CPC primary: H04L63/1433
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Systems and methods include: implementing a first machine learning model to generate an output of a global digital threat score for an online activity based on an input of the collected digital event data; implementing a second machine learning model that generates a category inference of a category of digital fraud or a category of digital abuse from a plurality of digital fraud or digital abuse categories; selecting a third machine learning model from an ensemble of digital fraud or digital abuse machine learning models based on the category inference generated by the second machine learning model, wherein the ensemble of digital fraud or digital abuse machine learning models comprise a plurality of disparate digital fraud or digital abuse category-specific machine learning models; and implementing the selected third machine learning model to generate a digital fraud or digital abuse category-specific threat score based on the digital event data.