US 11,809,565 B2
Security for private data inputs to artificial intelligence models
Abigail Reyes Knox, Oakville (CA); and Daniel Thomas Harrison, Newmarket (CA)
Assigned to Salesforce Inc., San Francisco, CA (US)
Filed by Salesforce Inc., San Francisco, CA (US)
Filed on Jan. 28, 2022, as Appl. No. 17/649,310.
Application 17/649,310 is a continuation of application No. 16/367,515, filed on Mar. 28, 2019, granted, now 11,256,809.
Prior Publication US 2022/0147633 A1, May 12, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. H04L 29/06 (2006.01); G06F 21/57 (2013.01); G06N 5/02 (2023.01)
CPC G06F 21/57 (2013.01) [G06N 5/02 (2013.01); G06F 2221/031 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for running an artificial intelligence model at a server, comprising:
running, in memory of the server, the artificial intelligence model on a public data set associated with a request and an extended data set associated with the request, the extended data set comprising the public data set and a set of private data associated with the request;
identifying a first set of outcomes based at least in part on running the artificial intelligence model on the public data set;
identifying a second set of outcomes based at least in part on running the artificial intelligence model on the extended data set;
comparing the first set of outcomes with the second set of outcomes to determine whether a difference between the first set of outcomes and the second set of outcomes satisfies a statistical threshold; and
transmitting, to a user device, a set of results based at least in part on comparing the first set of outcomes with the second set of outcomes.