Invention Grant
- Patent Title: Exploit prediction based on machine learning
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Application No.: US17693502Application Date: 2022-03-14
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Publication No.: US12079346B2Publication Date: 2024-09-03
- Inventor: Edward T. Bellis , Michael Roytman , Jeffrey Heuer
- Applicant: KENNA SECURITY LLC
- Applicant Address: US IL Chicago
- Assignee: KENNA SECURITY LLC
- Current Assignee: KENNA SECURITY LLC
- Current Assignee Address: US IL Chicago
- Agency: Baker Botts L.L.P.
- Main IPC: G06F21/57
- IPC: G06F21/57 ; G06N20/00

Abstract:
Generation of one or more models is caused based on selecting training data comprising a plurality of features including a prevalence feature for each vulnerability of a first plurality of vulnerabilities. The one or more models enable predicting whether an exploit will be developed for a vulnerability and/or whether the exploit will be used in an attack. The one or more models are applied to input data comprising the prevalence feature for each vulnerability of a second plurality of vulnerabilities. Based on the application of the one or more models to the input data, output data is received. The output data indicates a prediction of whether an exploit will be developed for each vulnerability of the second plurality. Additionally or alternatively, the output data indicates, for each vulnerability of the second plurality, a prediction of whether an exploit that has yet to be developed will be used in an attack.
Public/Granted literature
- US20220207152A1 Exploit Prediction Based on Machine Learning Public/Granted day:2022-06-30
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