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公开(公告)号：US11675928B2
公开(公告)日：2023-06-13
申请号：US16771359
申请日：2019-01-04
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Sungwook Kim , Hyejin Shin , Soohyung Kim , Chunghun Baek , Junbum Shin , Youngeun Lee , Kyungsun Cho
CPC classification number: G06F21/6254 , G06F21/16 , G06F21/602 , G06F21/64 , G06T1/0028
Abstract: Disclosed are an electronic device for obfuscating user data and a server for decoding the same. A method for controlling an electronic device according to the present disclosure comprises the steps of: acquiring a security parameter according to data transmitted to an external server; applying an obfuscation algorithm to the data by using the security parameter; and transmitting the data, to which the obfuscation algorithm has been applied, to the external server. Furthermore, in connection with a method for controlling a system comprising an electronic device for obfuscating data and a server for decoding the same according to the present disclosure, a method for controlling the electronic device comprises the steps of: inserting a fingerprint into data; generating multiple pieces of split data having a preset first size on the basis of the data into which the fingerprint has been inserted; applying an obfuscation algorithm to one piece of split data selected from the multiple pieces of split data by using a preset security parameter; and transmitting the split data, to which the obfuscation algorithm has been applied, to the server. In addition, a method for controlling the server comprises the steps of: receiving the multiple pieces of split data, to which the obfuscation algorithm has been applied, from the electronic device; acquiring at least one piece of candidate data on the basis of the received multiple pieces of split data, to which the obfuscation algorithm has been applied; and acquiring data comprising the fingerprint among the at least one piece of candidate data.
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公开(公告)号：US11605145B2
公开(公告)日：2023-03-14
申请号：US16362050
申请日：2019-03-22
Applicant: Samsung Electronics Co., Ltd.
Inventor： Kyungsun Cho , Jinsu Kim , Junbum Shin
Abstract: An electronic device is provided. The electronic device includes a camera, a memory configured to store a model learned to determine whether a user performing authentication for a financial service is in a threat situation, and a processor configured to perform authentication for the financial service based on biometrics information of the user performing authentication for the financial service. The processor may acquire an image by photographing the user performing authentication through the camera, acquire information on whether the user performing authentication is in a threat situation from the learned model, with information acquired from the image as input of the learned model, and perform authentication for the financial service according to the acquired information. At least a part of the learned model is an artificial intelligent algorithm, which may be performed according to at least one of machine learning, neural network, or deep learning algorithm.
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公开(公告)号：US11574375B2
公开(公告)日：2023-02-07
申请号：US16362050
申请日：2019-03-22
Applicant: Samsung Electronics Co., Ltd.
Inventor： Kyungsun Cho , Jinsu Kim , Junbum Shin
Abstract: An electronic device is provided. The electronic device includes a camera, a memory configured to store a model learned to determine whether a user performing authentication for a financial service is in a threat situation, and a processor configured to perform authentication for the financial service based on biometrics information of the user performing authentication for the financial service. The processor may acquire an image by photographing the user performing authentication through the camera, acquire information on whether the user performing authentication is in a threat situation from the learned model, with information acquired from the image as input of the learned model, and perform authentication for the financial service according to the acquired information. At least a part of the learned model is an artificial intelligent algorithm, which may be performed according to at least one of machine learning, neural network, or deep learning algorithm.
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