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公开(公告)号：US10341390B2
公开(公告)日：2019-07-02
申请号：US16170026
申请日：2018-10-24
Applicant: Google LLC
Inventor： Tal Dayan , Maya Ben Ari , Tanton Holt Gibbs , Ido Ofir , Jay Pierre Civelli , Brandon Keely , Christiaan Prins , Zheng Sun , Ning Zheng , James Brooks Miller , Jennifer Seth , Rongjing Xiang , Hugh Brendan McMahan
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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公开(公告)号：US20190068647A1
公开(公告)日：2019-02-28
申请号：US16170026
申请日：2018-10-24
Applicant: Google LLC
Inventor： Tal Dayan , Maya Ben Ari , Tanton Holt Gibbs , Ido Ofir , Jay Pierre Civelli , Brandon Keely , Christiaan Prins , Zheng Sun , Ning Zheng , James Brooks Miller , Jennifer Seth , Rongjing Xiang , Hugh Brendan McMahan
CPC classification number: H04L63/20 , H04W12/00503 , H04W12/00504 , H04W12/06 , H04W88/02
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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公开(公告)号：US10148692B2
公开(公告)日：2018-12-04
申请号：US14311376
申请日：2014-06-23
Applicant: Google LLC
Inventor： Tal Dayan , Maya Ben Ari , Tanton Holt Gibbs , Ido Ofir , Jay Pierre Civelli , Brandon Keely , Christiaan Prins , Zheng Sun , Ning Zheng , James Brooks Miller , Jennifer Fernquist , Rongjing Xiang , Hugh Brendan McMahan
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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