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US Patent 12015692 Enhanced encryption for face-related data

Patent 12015692 was granted and assigned to Verkada on June, 2024 by the United States Patent and Trademark Office.

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Patent Applicant
Verkada
Verkada
1
Current Assignee
Verkada
Verkada
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
120156921
Patent Inventor Names
Jose M. Giron Nanne1
Yuewei Wang1
Kiumars Soltani1
Kabir Chhabra1
Yunchao Gong1
Date of Patent
June 18, 2024
1
Patent Application Number
179370261
Date Filed
September 30, 2022
1
Patent Citations
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US Patent 11461551 Secure word search
1
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US Patent 11514714 Enhanced storage and data retrieval for face-related data
1
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US Patent 11496288 Enhanced encryption for face-related data
1
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US Patent 8972742 System for secure image recognition
1
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US Patent 10897351 Encryption key management for an automated workflow
1
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US Patent 11080316 Context-inclusive face clustering
1
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US Patent 11347868 Systems and methods for securely managing data in distributed systems
1
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US Patent 11354936 Incremental clustering for face recognition systems
1
Patent Primary Examiner
‌
Meng Li
1
CPC Code
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G06F 21/602
1
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H04L 9/3231
1
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H04L 9/008
1
Patent abstract

A method includes obtaining a plurality of representative vectors associated with face-related data. The method includes determining an encryption key based on a parameter stored in a record, generating an encrypted vector set by, for each respective vector of the plurality of representative vectors, encrypting the respective vector with a homomorphic encryption operation based on the encryption key, where the encrypted vector set includes a first encrypted vector that is linked to a subset of the face-related data associated with the first plurality of face vectors. The method further includes obtaining an encrypted face search vector using the encryption key to perform homomorphic encryption. The method further includes selecting a first encrypted vector based on the encrypted face search vector and retrieving the subset of the face-related data based on the first encrypted vector.

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