Deployment of Machine Learning Models for Discernment of Threats

A mismatch between model-based classifications produced by a first version of a machine learning threat discernment model and a second version of a machine learning threat discernment model for a file is detected. The mismatch is analyzed to determine appropriate handling for the file, and taking an...

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Bibliographische Detailangaben
Hauptverfasser: Rajamani Raj, Song Renee, Ipsen Kiefer, Sohn Alice, Rusell Braden, Harms Kristopher William
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung:A mismatch between model-based classifications produced by a first version of a machine learning threat discernment model and a second version of a machine learning threat discernment model for a file is detected. The mismatch is analyzed to determine appropriate handling for the file, and taking an action based on the analyzing. The analyzing includes comparing a human-generated classification status for a file, a first model version status that reflects classification by the first version of the machine learning threat discernment model, and a second model version status that reflects classification by the second version of the machine learning threat discernment model. The analyzing can also include allowing the human-generated classification status to dominate when it is available.