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US Patent 10552728 Automated anomaly detection for event-based system

Patent 10552728 was granted and assigned to Splunk on February, 2020 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
Splunk
Splunk
1
Current Assignee
Splunk
Splunk
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
105527281
Patent Inventor Names
Adam Oliner1
Sinduja Sreshta1
Zidong Yang1
Date of Patent
February 4, 2020
1
Patent Application Number
152244931
Date Filed
July 29, 2016
1
Patent Citations
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US Patent 10044751 Using recurrent neural networks to defeat DNS denial of service attacks
Patent Citations Received
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US Patent 12061563 Event recorder and method thereof
4
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US Patent 10956481 Event-based correlation of non-text machine data
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US Patent 11621971 Low-complexity detection of potential network anomalies using intermediate-stage processing
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US Patent 11636311 Anomaly detection based on predicted textual characters
7
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US Patent 11336507 Anomaly detection and filtering based on system logs
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US Patent 11314799 Event-based data intake and query system employing non-text machine data
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US Patent 11425232 Faulty distributed system component identification
1
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US Patent 10601849 Low-complexity detection of potential network anomalies using intermediate-stage processing
1
...
Patent Primary Examiner
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Kamran Afshar
1
Patent abstract

Described herein is a technology that facilitates the production of and the use of automated datagens for event-based systems. A datagen (i.e., data-generator or data generation system) is a component, module, or subsystem of computer systems that searches, monitors, and analyzes machine data. Existing datagens are not capable of detecting an anomaly in machine data. An anomaly is a variance in the input data stream that exceeds some acceptable amount of deviation from the norm (i.e., standard, expectation, etc.). An embodiment of datagen, in accordance with the technology described herein, detects anomalies in the input machine data.

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