Hardware, firmware, and software anomaly handling based on machine learning

Hardware, firmware, and software anomaly handling based on machine learning

Aspects of the invention include detecting an anomaly in a database of hardware, firmware, and software events. An exemplary method includes determining whether a previously addressed anomaly is a duplicate of the anomaly, addressing the anomaly according to a state of the previously addressed anoma...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: McCain, Edward C, Bhattacharya, Barin, Nettey, Jeffrey, Willoughby, Jeffrey
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:Aspects of the invention include detecting an anomaly in a database of hardware, firmware, and software events. An exemplary method includes determining whether a previously addressed anomaly is a duplicate of the anomaly, addressing the anomaly according to a state of the previously addressed anomaly based on the previously addressed anomaly being a duplicate of the anomaly, and addressing the anomaly according to machine learning based on the previously addressed anomaly not being the duplicate of the anomaly.