US 12,079,346 B2
Exploit prediction based on machine learning
Edward T. Bellis, Evanston, IL (US); Michael Roytman, Chicago, IL (US); and Jeffrey Heuer, New York, NY (US)
Filed by KENNA SECURITY LLC, Chicago, IL (US)
Filed on Mar. 14, 2022, as Appl. No. 17/693,502.
Application 17/693,502 is a continuation of application No. 17/008,515, filed on Aug. 31, 2020, granted, now 11,275,844.
Application 17/008,515 is a continuation of application No. 16/158,873, filed on Oct. 12, 2018, granted, now 10,762,212.
Application 16/158,873 is a continuation of application No. 15/827,943, filed on Nov. 30, 2017, granted, now 10,114,954.
Prior Publication US 2022/0207152 A1, Jun. 30, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 21/57 (2013.01); G06N 20/00 (2019.01)
CPC G06F 21/577 (2013.01) [G06N 20/00 (2019.01)] 18 Claims
OG exemplary drawing
 
1. A device, comprising:
one or more processors; and
one or more computer-readable non-transitory storage media coupled to the one or more processors and comprising instructions that, when executed by the one or more processors, cause the device to perform operations comprising:
receiving input data comprising one or more features for each software vulnerability of a plurality of software vulnerabilities;
causing application of a prediction model to the input data; and
generating, based on the application of the prediction model to the input data, output data, wherein:
the output data indicates a prediction of whether an exploit will be developed for each software vulnerability of the plurality of software vulnerabilities; and
the one or more features indicate a number of copies of software affected by each software vulnerability of the plurality of software vulnerabilities.