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US Patent 10291637 Network anomaly detection and profiling

Patent 10291637 was granted and assigned to Palantir Technologies on May, 2019 by the United States Patent and Trademark Office.

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Patent
Patent

Patent attributes

Patent Applicant
Palantir Technologies
Palantir Technologies
Current Assignee
Palantir Technologies
Palantir Technologies
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10291637
Date of Patent
May 14, 2019
Patent Application Number
15201856
Date Filed
July 5, 2016
Patent Citations Received
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US Patent 11930025 Threat detection and prevention for information systems
0
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US Patent 11336671 Method and apparatus for detecting anomaly in a plurality of devices by collectively analyzing information on devices
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US Patent 11782889 Systems and methods for continuous data profiling
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US Patent 11916944 Network anomaly detection and profiling
0
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US Patent 11533373 Global iterative clustering algorithm to model entities' behaviors and detect anomalies
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US Patent 10834103 Tracking and mitigation of an infected host device
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US Patent 11575688 Method of malware characterization and prediction
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US Patent 10992693 Near real-time detection of suspicious outbound traffic
...
Patent Primary Examiner
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Brandon S Hoffman
Patent abstract

A security system detects and attributes anomalous activity in a network. The system logs user network activity, which can include ports used, IP addresses, commands typed, etc., and may detect anomalous activity by comparing users to find similar users, sorting similar users into cohorts, and comparing new user activity to logged behavior of the cohort. The comparison can include a divergence calculation. Origins of user activity can also be used to determine anomalous network activity. The hostname, username, IP address, and timestamp can be used to calculate aggregate scores and convoluted scores. The system extracts features from the logged anomalous network activity, and determines whether the activity is attributable to an actor profile by comparing the extracted features and attributes associated with the actor profile based upon previous activity attributed to the actor.

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