The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 29, 2019

Filed:

May. 16, 2019
Applicant:

Sift Science, Inc., San Francisco, CA (US);

Inventors:

Fred Sadaghiani, San Francisco, CA (US);

Keren Gu, San Francisco, CA (US);

Vera Dadok, San Francisco, CA (US);

Alex Paino, San Francisco, CA (US);

Jacob Burnim, San Francisco, CA (US);

Assignee:

Sift Science, Inc., San Francisco, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 21/60 (2013.01); H04L 29/06 (2006.01); G06K 9/62 (2006.01); G06N 20/00 (2019.01); G06F 9/54 (2006.01); G06F 8/60 (2018.01);
U.S. Cl.
CPC ...
H04L 63/1425 (2013.01); G06F 8/60 (2013.01); G06F 9/542 (2013.01); G06K 9/6262 (2013.01); G06N 20/00 (2019.01); H04L 63/1441 (2013.01);
Abstract

Systems and methods include implementing a remote machine learning service that collects digital event data; collecting incumbent digital threat scores generated by an incumbent machine learning model and successor digital threat scores generated by a successor digital threat machine learning (ML) model; implementing anomalous-shift-detection that detects whether the successor digital threat scores of the successor digital threat ML model produces an anomalous shift; if the anomalous shift is detected by the machine learning model validation system, blocking a deployment of the successor digital threat model to a live ensemble of digital threat scoring models; or if the anomalous shift is not detected by the machine learning model validation system, deploying the successor digital threat ML model by replacing the incumbent digital threat ML model in a live ensemble of digital threat scoring models with the successor digital threat ML model.


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