Deployment of machine learning models for discernment of threats
First Claim
1. A method for implementation by one or more data processors forming part of at least one computing device, the method comprising:
- detecting, by at least one data processor, a mismatch between model-based classifications produced by a first version of a computer-implemented machine learning threat discernment model and a second version of a computer-implemented machine learning threat discernment model for a file, each of the first version of the machine learning threat discernment model and the second version of the machine learning threat discernment model for a file output a respective threat score based on a same set of features extracted from the file, wherein the mismatch is based on a difference between the respective threat scores; and
executing or accessing, by at least one data processor, the file if the difference between the respective threat scores is below a pre-defined threshold;
oranalyzing, by at least one data processor, the mismatch to determine appropriate handling for the file if the difference between the respective threat scores is equal to or above a pre-defined threshold.
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Accused Products
Abstract
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.
8 Citations
20 Claims
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1. A method for implementation by one or more data processors forming part of at least one computing device, the method comprising:
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detecting, by at least one data processor, a mismatch between model-based classifications produced by a first version of a computer-implemented machine learning threat discernment model and a second version of a computer-implemented machine learning threat discernment model for a file, each of the first version of the machine learning threat discernment model and the second version of the machine learning threat discernment model for a file output a respective threat score based on a same set of features extracted from the file, wherein the mismatch is based on a difference between the respective threat scores; and executing or accessing, by at least one data processor, the file if the difference between the respective threat scores is below a pre-defined threshold;
oranalyzing, by at least one data processor, the mismatch to determine appropriate handling for the file if the difference between the respective threat scores is equal to or above a pre-defined threshold. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A system comprising:
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at least one data processor; and memory storing instructions which, when executed by the at least one data processor, result in operations comprising; detecting a mismatch between model-based classifications produced by a first version of a computer-implemented machine learning threat discernment model and a second version of a computer-implemented machine learning threat discernment model for a file, each of the first version of the machine learning threat discernment model and the second version of the machine learning threat discernment model for a file output a respective threat score based on a same set of features extracted from the file, wherein the mismatch is based on a difference between the respective threat scores; and executing or accessing the file if the difference between the respective threat scores is below a pre-defined threshold;
oranalyzing the mismatch to determine appropriate handling for the file if the difference between the respective threat scores is equal to or above a pre-defined threshold. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A computer program product comprising non-transitory media storing instructions which, when executed by the at least one data processor, result in operations comprising:
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detecting a mismatch between model-based classifications produced by a first version of a computer-implemented machine learning threat discernment model and a second version of a computer-implemented machine learning threat discernment model for a file, each of the first version of the machine learning threat discernment model and the second version of the machine learning threat discernment model for a file output a respective threat score based on a same set of features extracted from the file, wherein the mismatch is based on a difference between the respective threat scores; and executing or accessing the file if the difference between the respective threat scores is below a pre-defined threshold;
oranalyzing the mismatch to determine appropriate handling for the file if the difference between the respective threat scores is equal to or above a pre-defined threshold. - View Dependent Claims (18, 19)
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20. The computer program product of 18, wherein the action comprises:
presenting the file via user interface functionality of an administrative interface with a choice of creating a new human-generated classification of the file as safe or allowing the second model version classification to govern when the file is deemed safe by the first model version but unsafe by the second model version, and when the human-generated classification is unavailable for the file.
Specification