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US Patent 11551137 Machine learning adversarial campaign mitigation on a computing device

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Is a
Patent
Patent
0

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
0
Patent Number
115511370
Patent Inventor Names
John Keith Kenemer0
Andrew B. Gardner0
Jasjeet Dhaliwal0
Javier Echauz0
Saurabh Shintre0
Date of Patent
January 10, 2023
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Patent Application Number
163997250
Date Filed
April 30, 2019
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Patent Citations
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US Patent 11057289 Mobile application identification in network traffic via a search engine approach
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US Patent 11240275 Platform and method for performing cybersecurity analyses employing an intelligence hub with a modular architecture
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US Patent 10764313 Method and system for protection against network-based cyber threats
Patent Citations Received
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US Patent 12026255 Machine learning model adversarial attack monitoring
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US Patent 12130943 Generative artificial intelligence model personally identifiable information detection and protection
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US Patent 12130917 GenAI prompt injection classifier training using prompt attack structures
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US Patent 12111926 Generative artificial intelligence model output obfuscation
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US Patent 12105844 Selective redaction of personally identifiable information in generative artificial intelligence model outputs
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US Patent 12107885 Prompt injection classifier using intermediate results
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US Patent 11757907 Cybersecurity threat intelligence and remediation system
Patent Primary Examiner
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Don G Zhao
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CPC Code
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G06K 9/6269
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G06K 9/623
0
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G06F 21/56
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G06N 20/00
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Machine learning adversarial campaign mitigation on a computing device. The method may include deploying an original machine learning model in a model environment associated with a client device; deploying a classification monitor in the model environment to monitor classification decision outputs in the machine learning model; detecting, by the classification monitor, a campaign of adversarial classification decision outputs in the machine learning model; applying a transformation function to the machine learning model in the model environment to transform the adversarial classification decision outputs to thwart the campaign of adversarial classification decision outputs; determining a malicious attack on the client device based in part on detecting the campaign of adversarial classification decision outputs; and implementing a security action to protect the computing device against the malicious attack.

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