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US Patent 10084805 Computer system to identify anomalies based on computer-generated results

Patent 10084805 was granted and assigned to Sas (company) on September, 2018 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Sas (company)
Sas (company)
Current Assignee
Sas (company)
Sas (company)
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10084805
Date of Patent
September 25, 2018
Patent Application Number
15897263
Date Filed
February 15, 2018
Patent Citations Received
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US Patent 12088477 System and method for predicting anomalous requests and preventing anomalous interactions in a network
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US Patent 11658881 System and method for predicting anomalous requests and preventing anomalous interactions in a network
0
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US Patent 11968109 Systems and methods for identifying correlations of certain scenarios to performance of network communications
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US Patent 11496386 Systems and methods for identifying correlations of certain scenarios to performance of network communications
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US Patent 10360069 Automated transfer of neural network definitions among federated areas
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US Patent 10565261 Many task computing with distributed file system
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US Patent 10642896 Handling of data sets during execution of task routines of multiple languages
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US Patent 10649750 Automated exchanges of job flow objects between federated area and external storage space
...
Patent Primary Examiner
Haresh N Patel
Haresh N Patel
Patent abstract

One or more embodiments may include techniques to identify anomalies based on computer-generated results. Moreover, embodiments may include applying scenario rules to data to detect scenario violations and grouping the scenario violations into scenario clusters based on similar behavior performed by entities indicated by similarity metrics. embodiments include determining predictive ability values for each of the scenario clusters, ranking the scenario clusters based on the predictive ability values, and removing scenario clusters having predictive ability values below a threshold. In embodiments combinations of scenario clusters may be generated from the set of scenario clusters and the combinations of scenario clusters may be evaluated for effectiveness. Embodiments include generating scores for entities of the combinations of scenario clusters deemed effective, and provide results indicating whether one or more of the entities committed an anomaly based on the scores for each of the entities.

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