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:
Dec. 12, 2023

Filed:

Sep. 07, 2022
Applicant:

Tripleblind, Inc., Kansas City, MO (US);

Inventors:

Babak Poorebrahim Gilkalaye, Kansas City, MO (US);

Gharib Gharibi, Overland Park, KS (US);

Greg Storm, Kansas City, MO (US);

Riddhiman Das, Parkville, MO (US);

Assignee:

TripleBlind, Inc., Kansas City, MO (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 9/40 (2022.01); G06N 3/082 (2023.01); H04L 9/00 (2022.01); G06F 17/16 (2006.01); G06N 3/04 (2023.01); H04L 9/06 (2006.01); G06F 18/24 (2023.01); G06F 18/2113 (2023.01); G06N 3/098 (2023.01); G06N 3/048 (2023.01); G06F 16/13 (2019.01); G06F 21/62 (2013.01);
U.S. Cl.
CPC ...
H04L 63/0428 (2013.01); G06F 16/13 (2019.01); G06F 17/16 (2013.01); G06F 18/2113 (2023.01); G06F 18/24 (2023.01); G06F 21/6245 (2013.01); G06N 3/04 (2013.01); G06N 3/048 (2023.01); G06N 3/082 (2013.01); G06N 3/098 (2023.01); H04L 9/008 (2013.01); H04L 9/0625 (2013.01); H04L 2209/46 (2013.01);
Abstract

A system and method for securely computing an inference of two types of tree-based models, namely XGBoost and Random Forest, using secure multi-party computation protocol. The method includes computing a respective comparison result of each respective node of a plurality of nodes in a tree classifier. Each node has a respective threshold value. The respective comparison result is based on respective data associated with a data owner device being applied to a respective node having the respective threshold value. The method includes computing, based on the respective comparison result, a leaf value associated with the tree classifier, generating a share of the leaf value and transmitting, to the data owner device, a share of the leaf value. The data owner device computes, using a secure multi-party computation and between the model owner device and the data owner device, the leaf value for the respective data of the data owner.


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