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US Patent 12073300 Systems and methods for post-quantum cryptography optimization

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Contents

Is a
Patent
Patent
0

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
120733000
Patent Inventor Names
Andrew J. Garner, IV0
Pierre Arbajian0
Michael Erik Meinholz0
Date of Patent
August 27, 2024
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Patent Application Number
183367600
Date Filed
June 16, 2023
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Patent Citations
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US Patent 8539586 Method for evaluating system risk
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US Patent 9960465 Battery pack
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US Patent 10003457 Random cipher pad cryptography
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US Patent 10015187 System and method for performing remote security assessment of firewalled computer
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US Patent 10016187 Articulating surgical instruments and method of deploying the same
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US Patent 10021140 Advanced asset tracking and correlation
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US Patent 10057058 Quantum-key distribution apparatus, quantum-key distribution method, and computer program product
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US Patent 10089489 Transparent client application to arbitrate data storage between mutable and immutable data repositories
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Patent Primary Examiner
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Peter C Shaw
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CPC Code
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H04L 9/3013
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H04L 9/302
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G06N 20/00
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G06N 5/04
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H04L 9/0852
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H04L 9/0891
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Patent abstract

Systems, apparatuses, methods, and computer program products are disclosed for post-quantum cryptography (PQC). An example method includes receiving data. The example method further includes receiving a set of data attributes about the data. The set of data attributes comprises one or more sets of data environment data attributes that are each representative of a set of data environments associated with the data. The example method further includes receiving one or more sets of data environment threat data structures associated with one or more data environments in the one or more sets of data environments associated with the data. The example method further includes selecting one or more cryptographic techniques for encrypting the data for at least the one or more data environments based on the set of data attributes, the one or more sets of data environment threat data structures, and a cryptograph optimization machine learning model.

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