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公开(公告)号：US20170332197A1
公开(公告)日：2017-11-16
申请号：US15651536
申请日：2017-07-17
Applicant: Amazon Technologies, Inc.
Inventor： Keerat Singh Sharma , Guthrie Chipman Collin , Chesley Bernard Coughlin , Timothy John Craycroft , Gerard Gjonej , Pramod Raghavendran
CPC classification number: H04W4/021 , H04W4/025 , H04W4/029 , H04W12/00502 , H04W12/00503 , H04W12/02
Abstract: Various approaches discussed herein enable techniques for managing privacy with respect to location-based operations, for example by receiving point of interest (POI) data corresponding to location data such as global positioning service (GPS) data at a computing device along with various location-based rules, which when satisfied, result in attribution events being generated that indicate various characteristics associated with POIs in the POI data. The attribution events are then sent to a server without compromising the location privacy of the computing device, because the location of the computing device is not included with the attribution events.
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公开(公告)号：US11606339B1
公开(公告)日：2023-03-14
申请号：US17185796
申请日：2021-02-25
Applicant: Amazon Technologies, Inc.
Inventor： Paul A. Kotas , Keerat Singh Sharma , Matthew H. Battles
IPC: H04L9/40
Abstract: A privacy protecting transaction engine for a cloud provider network is described. According to some embodiments, a computer-implemented method includes receiving a request from a customer of a cloud provider network to create a customer cloud in the cloud provider network, generating the customer cloud in the cloud provider network, receiving a first request at the cloud provider network for the customer cloud that includes private information of an end customer of the customer of the cloud provider network, removing the private information from the first request by a privacy protecting transaction engine of the cloud provider network to generate a second request, and sending the second request to the customer cloud for servicing.
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公开(公告)号：US20170180928A1
公开(公告)日：2017-06-22
申请号：US14976688
申请日：2015-12-21
Applicant: Amazon Technologies, Inc.
Inventor： Keerat Singh Sharma , Guthrie Chipman Collin , Chesley Bernard Coughlin , Timothy John Craycroft , Gerard Gjonej , Pramod Raghavendran
Abstract: Various approaches discussed herein enable techniques for managing privacy with respect to location-based operations, for example by receiving point of interest (POI) data corresponding to location data such as global positioning service (GPS) data at a computing device along with various location-based rules, which when satisfied, result in attribution events being generated that indicate various characteristics associated with POIs in the POI data. The attribution events are then sent to a server without compromising the location privacy of the computing device, because the location of the computing device is not included with the attribution events.
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公开(公告)号：US09578044B1
公开(公告)日：2017-02-21
申请号：US14223544
申请日：2014-03-24
Applicant: Amazon Technologies, Inc.
CPC classification number: H04L63/1416
Abstract: Systems, methods, and computer-readable media are disclosed for detecting anomalous advertising content and taking or directing one or more actions to be taken to mitigate risk associated with anomalous advertising content. The anomalous advertising content indicates a deviation from an expected state of the advertising content. Various measures may be taken to determine whether the anomalous advertising content is reflective of malware.
Abstract translation: 公开了系统，方法和计算机可读介质，用于检测异常广告内容并采取或指导要采取的一个或多个动作以减轻与异常广告内容相关联的风险。 异常广告内容表示偏离广告内容的预期状态。 可以采取各种措施来确定异常广告内容是否反映恶意软件。
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Patent Agency Ranking
公开(公告)号：US12041035B1
公开(公告)日：2024-07-16
申请号：US18165724
申请日：2023-02-07
Applicant: Amazon Technologies, Inc.
Inventor： Paul A. Kotas , Keerat Singh Sharma , Matthew H. Battles
IPC: H04L9/40
CPC classification number: H04L63/0414
Abstract: A privacy protecting transaction engine for a cloud provider network is described. According to some embodiments, a computer-implemented method includes receiving a request from a customer of a cloud provider network to create a customer cloud in the cloud provider network, generating the customer cloud in the cloud provider network, receiving a first request at the cloud provider network for the customer cloud that includes private information of an end customer of the customer of the cloud provider network, removing the private information from the first request by a privacy protecting transaction engine of the cloud provider network to generate a second request, and sending the second request to the customer cloud for servicing.
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公开(公告)号：US09712964B2
公开(公告)日：2017-07-18
申请号：US14976688
申请日：2015-12-21
Applicant: Amazon Technologies, Inc.
Inventor： Keerat Singh Sharma , Guthrie Chipman Collin , Chesley Bernard Coughlin , Timothy John Craycroft , Gerard Gjonej , Pramod Raghavendran
Abstract: Various approaches discussed herein enable techniques for managing privacy with respect to location-based operations, for example by receiving point of interest (POI) data corresponding to location data such as global positioning service (GPS) data at a computing device along with various location-based rules, which when satisfied, result in attribution events being generated that indicate various characteristics associated with POIs in the POI data. The attribution events are then sent to a server without compromising the location privacy of the computing device, because the location of the computing device is not included with the attribution events.
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公开(公告)号：US11997209B1
公开(公告)日：2024-05-28
申请号：US17208881
申请日：2021-03-22
Applicant: Amazon Technologies, Inc.
Inventor： Rahul Chopra , Maurice Lin , Pramod Raghavendran , Keerat Singh Sharma
CPC classification number: H04L9/3236 , H04L9/50
Abstract: Devices, systems, and methods are provided for rotating cryptography secrets in data hashing. A method may include generating, based on a hashing technique, first obfuscated data using first data and a first version of a secret, and generating first metadata associated with the first obfuscated data, the first metadata indicative of the first version of the secret. The method may include determining a second version of the secret based on the first metadata. The method may include generating, based on the hashing technique, second obfuscated data using the first obfuscated data and the second version of the secret, and generating second metadata associated with the second obfuscated data, the second metadata indicative of the second version of the secret.
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公开(公告)号：US11922456B1
公开(公告)日：2024-03-05
申请号：US17954758
申请日：2022-09-28
Applicant: Amazon Technologies, Inc.
Inventor： Anthony Crider , Hariharan Jayaraman , Nicole Landis Ferragonio , Alan Kerry Lewis , Keerat Singh Sharma
IPC: G06Q30/02 , G06Q30/0242
CPC classification number: G06Q30/0246
Abstract: Data clean rooms provided for subscribers to advertising analysis services include data regarding advertising impressions, selections, view or conversion events, and memberships of audience segments, and computing functions or capacities for processing the data in an anonymized fashion. When advertisements are presented to customers, and interactions by customers (e.g., impressions, views, clicks, conversions or others) with goods or services are detected, data regarding the interactions may be aggregated and stored. When queries on behalf of an advertiser are identified, data associated with the queries may be retrieved and stored in a data clean room for processing or analysis. Anonymized responses to the query may be returned to the customer or serve as basis for one or more advertising events.
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公开(公告)号：US10484429B1
公开(公告)日：2019-11-19
申请号：US15335175
申请日：2016-10-26
Applicant: Amazon Technologies, Inc.
Inventor： John Kenneth Fawcett , Joe Jony Jeyaratnam , Pramod Raghavendran , Martin Christopher Hare Robertson , Keerat Singh Sharma
IPC: H04L29/06
Abstract: Systems, methods, and computer-readable media are disclosed for automated sensitive information and data storage compliance verification. In one embodiment, an example method may include determining a software application stored at a database, determining software code of the software application, and determining that the software code includes a function that accesses critical user information. Example methods may include determining a risk score for the software application based at least in part on the function, and determining a compliance level for the software application based at least in part on the function.
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