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. 04, 2018

Filed:

Jun. 23, 2014
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Tal Dayan, Los Gatos, CA (US);

Maya Ben Ari, Palo Alto, CA (US);

Tanton Holt Gibbs, Redmond, WA (US);

Ido Ofir, Los Altos, CA (US);

Jay Pierre Civelli, Sunnyvale, CA (US);

Brandon Keely, San Francisco, CA (US);

Christiaan Prins, San Francisco, CA (US);

Zheng Sun, Mountain View, CA (US);

Ning Zheng, Mountain View, CA (US);

James Brooks Miller, Sunnyvale, CA (US);

Jennifer Fernquist, San Francisco, CA (US);

Rongjing Xiang, Mountain View, CA (US);

Hugh Brendan McMahan, Seattle, WA (US);

Assignee:

Google LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04W 12/06 (2009.01); H04L 29/06 (2006.01); H04W 88/02 (2009.01);
U.S. Cl.
CPC ...
H04L 63/20 (2013.01); H04W 12/06 (2013.01); H04W 88/02 (2013.01);
Abstract

Systems and techniques are provided for aggregation of asynchronous trust outcomes in a mobile device. Trust levels may be determined from the signals. Each trust level may be determined independently of any other trust level. Each trust level may be determined based on applying to the signals heuristics, mathematical optimization, decisions trees, machine learning systems, or artificial intelligence systems. An aggregated trust outcome may be determined by aggregating the trust levels. Aggregating the trust levels may include applying heuristics, mathematical optimization, decisions trees, machine learning systems, or artificial intelligence systems to the trust levels, and wherein the aggregated trust outcome; and sending the aggregated trust outcome to be implemented by the enabling, disabling, or relaxing of at least one security measure based on the aggregated trust outcome.


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