公开(公告)号：US09866555B2

公开(公告)日：2018-01-09

申请号：US14757769

申请日：2015-12-23

Applicant: INTEL CORPORATION

Inventor： Micah J. Sheller ,  Yonghong Huang ,  Narjala P. Bhasker ,  Jason Martin ,  Cory Cornelius

IPC: G06F7/04 ,  G06F15/16 ,  G06F17/30 ,  H04L29/06 ,  G06F21/30 ,  H04W12/08 ,  G06F3/01 ,  G06F1/16

CPC classification number: H04L63/0876 ,  G06F1/163 ,  G06F3/01 ,  G06F3/014 ,  G06F3/017 ,  G06F21/30 ,  G06F21/305 ,  H04L63/0492 ,  H04L63/0853 ,  H04W12/06 ,  H04W12/08

Abstract: Various embodiments are generally directed to an apparatus, method, and other techniques to maintain user authentications with common trusted devices. If a user is in possession of a first computing device (e.g., a smartphone), an unlocked state of the first trusted device is maintained if the user is using a nearby trusted device (e.g., a computer) within a certain amount of time. If the first trusted device is in a pocket or other container, a longer span of time is granted to the user to register an on-body state.

公开(公告)号：US11556730B2

公开(公告)日：2023-01-17

申请号：US15942131

申请日：2018-03-30

Applicant: Intel Corporation

Inventor： Micah Sheller ,  Cory Cornelius

IPC: G06K9/62 ,  H04L67/10 ,  G06N20/00 ,  G06F16/951 ,  G06N3/063 ,  G06F21/62 ,  G06N3/04 ,  G06F21/74 ,  G06N3/08 ,  G06N99/00

Abstract: Methods, apparatus, systems and articles of manufacture for distributed use of a machine learning model are disclosed. An example edge device includes a model partitioner to partition a machine learning model received from an aggregator into private layers and public layers. A public model data store is implemented outside of a trusted execution environment of the edge device. The model partitioner is to store the public layers in the public model data store. A private model data store is implemented within the trusted execution environment. The model partitioner is to store the private layers in the private model data store.

公开(公告)号：US20190042878A1

公开(公告)日：2019-02-07

申请号：US15942131

申请日：2018-03-30

Applicant: Intel Corporation

Inventor： Micah Sheller ,  Cory Cornelius

IPC: G06K9/62 ,  G06N99/00 ,  H04L29/08 ,  G06F17/30

Abstract: Methods, apparatus, systems and articles of manufacture for distributed use of a machine learning model are disclosed. An example edge device includes a model partitioner to partition a machine learning model received from an aggregator into private layers and public layers. A public model data store is implemented outside of a trusted execution environment of the edge device. The model partitioner is to store the public layers in the public model data store. A private model data store is implemented within the trusted execution environment. The model partitioner is to store the private layers in the private model data store.

公开(公告)号：US20180239976A1

公开(公告)日：2018-08-23

申请号：US15439224

申请日：2017-02-22

Applicant: Intel Corporation

Inventor： Cory Cornelius ,  Jason Martin ,  Ramune Nagisetty ,  Micah J. Sheller ,  Thao W. Xiong ,  Reese Bowes

IPC: G06K9/00 ,  G06T7/11 ,  G06K9/62 ,  G06F1/16 ,  H04L29/06

Abstract: In one embodiment, an apparatus includes: a bioimpedance sensor to generate bioimpedance information based on bioimpedance sample information from at least some of a plurality of electrodes to be adapted about a portion of a person; at least one biometric sensor to generate biometric information based on biometric sample information from at least some of the plurality of electrodes; at least one environmental sensor to generate environmental context data; and an integration circuit to receive the bioimpedance information, the biometric information and the environmental context data and to adjust the bioimpedance information based at least in part on a value of one or more of the biometric information and the environmental context data. Other embodiments are described and claimed.

公开(公告)号：US20160306955A1

公开(公告)日：2016-10-20

申请号：US14859611

申请日：2015-09-21

Applicant: Intel Corporation

Inventor： Jason Martin ,  Rahuldeva Ghosh ,  Cory Cornelius ,  Ian R. Oliver ,  Ramune Nagisetty ,  Steven B. McGowan

IPC: G06F21/34 ,  G06F21/35

CPC classification number: G06F21/34 ,  G06F21/00 ,  G06F21/35

Abstract: In one embodiment, a first device includes: a first logic to generate a first token when a user adapts the first device in approximate contact to the user, the first token including a first timestamp; a storage to store the first token and a second token, the second token obtained from an authenticator and associated with an authentication of the user to a second device, the second token including a second timestamp; and a communication module to communicate the first and second tokens to the second device to cause the second device to authenticate the user based at least in part on the first and second tokens. Other embodiments are described and claimed.

Abstract translation: 在一个实施例中，第一设备包括：第一逻辑，用于当用户以与用户近似接触的方式适配第一设备时生成第一令牌，第一令牌包括第一时间戳; 用于存储所述第一令牌和第二令牌的存储器，所述第二令牌从认证器获得并与所述用户的认证相关联到第二设备，所述第二令牌包括第二时间戳; 以及通信模块，用于将第一和第二令牌传送到第二设备，以使得第二设备至少部分地基于第一和第二令牌来认证用户。 描述和要求保护其他实施例。

公开(公告)号：US12169584B2

公开(公告)日：2024-12-17

申请号：US18070299

申请日：2022-11-28

Applicant: INTEL CORPORATION

Inventor： Micah Sheller ,  Cory Cornelius

IPC: G06F21/62 ,  G06F16/951 ,  G06F18/21 ,  G06F18/2411 ,  G06F21/74 ,  G06N3/04 ,  G06N3/045 ,  G06N3/063 ,  G06N3/08 ,  G06N20/00 ,  G06N99/00 ,  H04L67/10

Abstract: Methods, apparatus, systems and articles of manufacture for distributed use of a machine learning model are disclosed. An example edge device includes a model partitioner to partition a machine learning model received from an aggregator into private layers and public layers. A public model data store is implemented outside of a trusted execution environment of the edge device. The model partitioner is to store the public layers in the public model data store. A private model data store is implemented within the trusted execution environment. The model partitioner is to store the private layers in the private model data store.

公开(公告)号：US20240330466A1

公开(公告)日：2024-10-03

申请号：US18676413

申请日：2024-05-28

Applicant: Intel Corporation

Inventor： Scott Douglas Constable ,  Marcin Andrzej Chrapek ,  Marcin Spoczynski ,  Cory Cornelius ,  Mona Vij ,  Anjo Lucas Vahldiek-Oberwagner

IPC: G06F21/57

CPC classification number: G06F21/57

Abstract: Methods, apparatus, systems, and articles of manufacture to verify integrity of a model are disclosed. An example apparatus includes programmable circuitry to initialize an instance of a trusted execution environment; upload a security manifest of the trusted execution environment and a machine learning model; determine whether to store the machine learning model into a memory based on checking of the security manifest; determine whether the machine learning model is valid; and output a validation result.

公开(公告)号：US11657162B2

公开(公告)日：2023-05-23

申请号：US16361397

申请日：2019-03-22

Applicant: Intel Corporation

Inventor： Michael Kounavis ,  Antonios Papadimitriou ,  Anindya Sankar Paul ,  Micah Sheller ,  Li Chen ,  Cory Cornelius ,  Brandon Edwards

IPC: G06F21/60 ,  G06N3/08 ,  G06N3/04 ,  G06F21/52

CPC classification number: G06F21/60 ,  G06F21/52 ,  G06N3/0454 ,  G06N3/08

Abstract: In one example an apparatus comprises a memory and a processor to create, from a first deep neural network (DNN) model, a first plurality of DNN models, generate a first set of adversarial examples that are misclassified by the first plurality of deep neural network (DNN) models, determine a first set of activation path differentials between the first plurality of adversarial examples, generate, from the first set of activation path differentials, at least one composite adversarial example which incorporates at least one intersecting critical path that is shared between at least two adversarial examples in the first set of adversarial examples, and use the at least one composite adversarial example to generate a set of inputs for a subsequent training iteration of the DNN model. Other examples may be described.

公开(公告)号：US11526745B2

公开(公告)日：2022-12-13

申请号：US15892138

申请日：2018-02-08

Applicant: Intel Corporation

Inventor： Micah Sheller ,  Cory Cornelius ,  Jason Martin ,  Yonghong Huang ,  Shih-Han Wang

IPC: G06F21/55 ,  G06N3/08 ,  G06N3/063

Abstract: Methods, apparatus, systems and articles of manufacture for federated training of a neural network using trusted edge devices are disclosed. An example system includes an aggregator device to aggregate model updates provided by one or more edge devices. The one or more edge devices to implement respective neural networks, and provide the model updates to the aggregator device. At least one of the edge devices to implement the neural network within a trusted execution environment.

公开(公告)号：US10511600B2

公开(公告)日：2019-12-17

申请号：US15865063

申请日：2018-01-08

Applicant: INTEL CORPORATION

Inventor： Micah J. Sheller ,  Yonghong Huang ,  Narjala P. Bhasker ,  Jason Martin ,  Cory Cornelius

IPC: H04L29/06 ,  G06F21/20 ,  H04W12/00 ,  H04W12/06 ,  H04W12/08 ,  G06F1/16 ,  G06F3/01 ,  G06F21/30

Abstract: Various embodiments are generally directed to an apparatus, method, and other techniques to maintain user authentications with common trusted devices. If a user is in possession of a first computing device (e.g., a smartphone), an unlocked state of the first trusted device is maintained if the user is using a nearby trusted device (e.g., a computer) within a certain amount of time. If the first trusted device is in a pocket or other container, a longer span of time is granted to the user to register an on-body state.