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US Patent 11546360 Cyber security appliance for a cloud infrastructure

Patent 11546360 was granted and assigned to Darktrace on January, 2023 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
Darktrace
Darktrace
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Current Assignee
Darktrace
Darktrace
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
115463600
Patent Inventor Names
Jacob Araiza0
Alex Markham0
Andrew Woodford0
Matthew Dunn0
Date of Patent
January 3, 2023
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Patent Application Number
162789820
Date Filed
February 19, 2019
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Patent Citations
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US Patent 10498605 Cloud based systems and methods for determining and visualizing security risks of companies, users, and groups
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Patent Citations Received
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US Patent 11841945 System and method for cybersecurity threat detection utilizing static and runtime data
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US Patent 11936785 System and method for encrypted disk inspection utilizing disk cloning techniques
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US Patent 11954516 Techniques for inspecting managed workloads deployed in a cloud computing environment
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US Patent 12001585 System and method for agentless detection of sensitive data in computing environments
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US Patent 12003630 Techniques for circumventing provider-imposed limitations in snapshot inspection of disks for cybersecurity
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US Patent 12061719 System and method for agentless detection of sensitive data in computing environments
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US Patent 12061925 Techniques for inspecting managed workloads deployed in a cloud computing environment
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US Patent 12081656 Techniques for circumventing provider-imposed limitations in snapshot inspection of disks for cybersecurity
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Patent Primary Examiner
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Sakinah White Taylor
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A cyber security appliance has modules that utilize probes to interact with entities in a cloud infrastructure environment (CIE). A cloud module can 1) use the information about relevant changes in the CIE fed from the probes, and 2) use machine learning models that are trained on a normal behavior of at least a first entity associated with the CIE; and thus, indicate when a behavior of the first entity falls outside of being a normal pattern of life. A cyber threat module can use machine learning models trained on cyber threats in the CIE and examine at least the behaviors of the first entity falling outside of the normal pattern of life to determine what is a likelihood of ‘a chain of unusual behaviors under analysis that fall outside of being the normal behavior’ is a cyber threat. An autonomous response module can cause actions to contain the cyber threat.

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