Patent · US Active

Systems and methods for machine learning-based detection of an automated fraud attack or an automated abuse attack

US11777962B2 · kind B2 · utility

0Cited by

1References

20Claims

0Family size

Assignee

Sift Science, Inc. · US

Inventors

Kostyantyn Gurnov · San Francisco, US
Wei Liu · Schenectady, US
Nicholas Benavides · Washington, US
Volha Leusha · San Francisco, US
Yanqing Bao · San Francisco, US
Louie Zhang · San Francisco, US
Irving Chen · Sha Tin, CN
Logan Davis · San Francisco, US
Andy Cai · San Francisco, US

Key dates

Filing date	Dec 18, 2022
Grant date	Oct 3, 2023
Priority date	—
Expiry date	Dec 18, 2042

Classification

Technology area (CPC G)Physics
CPC primaryG06N20/00
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A method for machine learning-based detection of an automated fraud or abuse attack includes: identifying, via a computer network, a digital event associated with a suspected automated fraud or abuse attack; composing, via one or more computers, a digital activity signature of the suspected automated fraud or abuse attack based on digital activity associated with the suspected automated fraud or abuse attack; computing, via a machine learning model, an encoded representation of the digital activity signature; searching, via the one or more computers, an automated fraud or abuse signature registry based on the encoded representation of the digital activity signature; determining a likely origin of the digital event based on the searching of the automated fraud or abuse signature registry; and selectively implementing one or more automated threat mitigation actions based on the likely origin of the digital event.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.