- Patent Title: Machine learning model score obfuscation using multiple classifiers
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Application No.: US16399665Application Date: 2019-04-30
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Publication No.: US11586975B2Publication Date: 2023-02-21
- Inventor: David N. Beveridge , Hailey Buckingham
- Applicant: Cylance Inc.
- Applicant Address: US CA Irvine
- Assignee: Cylance Inc.
- Current Assignee: Cylance Inc.
- Current Assignee Address: US CA Irvine
- Agency: Jones Day
- Main IPC: G06F21/56
- IPC: G06F21/56 ; G06F21/14 ; G06N20/00 ; G06N5/048

Abstract:
An artefact is received. Thereafter, features are extracted from the artefact and a vector is populated. Later, one of a plurality of available classification models is selected. The classification models use different scoring paradigms while providing the same or substantially similar classifications. The vector is input into the selected classification model to generate a score. The score is later provided to a consuming application or process. The classification model can characterize the artefact as being malicious or benign to access, execute, or continue to execute so that appropriate remedial action can be taken or initiated by the consuming application or process. Related apparatus, systems, techniques and articles are also described.
Public/Granted literature
- US20200349461A1 Machine Learning Model Score Obfuscation Using Multiple Classifiers Public/Granted day:2020-11-05
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