Patents by Inventor Kevin A. Beets
Kevin A. Beets has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11157617Abstract: In accordance with one embodiment of the present disclosure, a method for determining the similarity between a first data set and a second data set is provided. The method includes performing an entropy analysis on the first and second data sets to produce a first entropy result, wherein the first data set comprises data representative of a first one or more computer files of known content and the second data set comprises data representative of a one or more computer files of unknown content; analyzing the first entropy result; and if the first entropy result is within a predetermined threshold, identifying the second data set as substantially related to the first data set.Type: GrantFiled: September 19, 2019Date of Patent: October 26, 2021Assignee: McAfee, LLCInventors: David Neill Beveridge, Abhishek Ajay Karnik, Kevin A. Beets, Tad M. Heppner, Karthik Raman
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Patent number: 11126719Abstract: In one respect, there is provided a system for classifying malware. The system may include a data processor and a memory. The memory may include program code that provides operations when executed by the processor. The operations may include: providing, to a display, contextual information associated with a file to at least enable a classification of the file, when a malware classifier is unable to classify the file; receiving, in response to the providing of the contextual information, the classification of the file; and updating, based at least on the received classification of the file, the malware classifier to enable the malware classifier to classify the file. Methods and articles of manufacture, including computer program products, are also provided.Type: GrantFiled: May 31, 2019Date of Patent: September 21, 2021Assignee: Cylance Inc.Inventors: Matthew Maisel, Ryan Permeh, Matthew Wolff, Gabriel Acevedo, Andrew Davis, John Brock, Homer Valentine Strong, Michael Wojnowicz, Kevin Beets
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Publication number: 20200012792Abstract: In accordance with one embodiment of the present disclosure, a method for determining the similarity between a first data set and a second data set is provided. The method includes performing an entropy analysis on the first and second data sets to produce a first entropy result, wherein the first data set comprises data representative of a first one or more computer files of known content and the second data set comprises data representative of a one or more computer files of unknown content; analyzing the first entropy result; and if the first entropy result is within a predetermined threshold, identifying the second data set as substantially related to the first data set.Type: ApplicationFiled: September 19, 2019Publication date: January 9, 2020Inventors: David Neill Beveridge, Abhishek Ajay Karnik, Kevin A. Beets, Tad M. Heppner, Karthik Raman
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Patent number: 10423786Abstract: In accordance with one embodiment of the present disclosure, a method for determining the similarity between a first data set and a second data set is provided. The method includes performing an entropy analysis on the first and second data sets to produce a first entropy result, wherein the first data set comprises data representative of a first one or more computer files of known content and the second data set comprises data representative of a one or more computer files of unknown content; analyzing the first entropy result; and if the first entropy result is within a predetermined threshold, identifying the second data set as substantially related to the first data set.Type: GrantFiled: November 15, 2016Date of Patent: September 24, 2019Assignee: McAfee, LLCInventors: David Neill Beveridge, Abhishek Ajay Karnik, Kevin A. Beets, Tad M. Heppner, Karthik Raman
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Publication number: 20190286819Abstract: In one respect, there is provided a system for classifying malware. The system may include a data processor and a memory. The memory may include program code that provides operations when executed by the processor. The operations may include: providing, to a display, contextual information associated with a file to at least enable a classification of the file, when a malware classifier is unable to classify the file; receiving, in response to the providing of the contextual information, the classification of the file; and updating, based at least on the received classification of the file, the malware classifier to enable the malware classifier to classify the file. Methods and articles of manufacture, including computer program products, are also provided.Type: ApplicationFiled: May 31, 2019Publication date: September 19, 2019Inventors: Matthew Maisel, Ryan Permeh, Matthew Wolff, Gabriel Acevedo, Andrew Davis, John Brock, Homer Valentine Strong, Michael Wojnowicz, Kevin Beets
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Patent number: 10360380Abstract: In one respect, there is provided a system for classifying malware. The system may include a data processor and a memory. The memory may include program code that provides operations when executed by the processor. The operations may include: providing, to a display, contextual information associated with a file to at least enable a classification of the file, when a malware classifier is unable to classify the file; receiving, in response to the providing of the contextual information, the classification of the file; and updating, based at least on the received classification of the file, the malware classifier to enable the malware classifier to classify the file. Methods and articles of manufacture, including computer program products, are also provided.Type: GrantFiled: January 19, 2017Date of Patent: July 23, 2019Assignee: Cylance Inc.Inventors: Matthew Maisel, Ryan Permeh, Matthew Wolff, Gabriel Acevedo, Andrew Davis, John Brock, Homer Strong, Michael Wojnowicz, Kevin Beets
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Publication number: 20180203998Abstract: In one respect, there is provided a system for classifying malware. The system may include a data processor and a memory. The memory may include program code that provides operations when executed by the processor. The operations may include: providing, to a display, contextual information associated with a file to at least enable a classification of the file, when a malware classifier is unable to classify the file; receiving, in response to the providing of the contextual information, the classification of the file; and updating, based at least on the received classification of the file, the malware classifier to enable the malware classifier to classify the file. Methods and articles of manufacture, including computer program products, are also provided.Type: ApplicationFiled: January 19, 2017Publication date: July 19, 2018Inventors: Matthew Maisel, Ryan Permeh, Matthew Wolff, Gabriel Acevedo, Andrew Davis, John Brock, Homer Strong, Michael Wojnowicz, Kevin Beets
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Publication number: 20170061125Abstract: In accordance with one embodiment of the present disclosure, a method for determining the similarity between a first data set and a second data set is provided. The method includes performing an entropy analysis on the first and second data sets to produce a first entropy result, wherein the first data set comprises data representative of a first one or more computer files of known content and the second data set comprises data representative of a one or more computer files of unknown content; analyzing the first entropy result; and if the first entropy result is within a predetermined threshold, identifying the second data set as substantially related to the first data set.Type: ApplicationFiled: November 15, 2016Publication date: March 2, 2017Inventors: David Neill Beveridge, Abhishek Ajay Karnik, Kevin A. Beets, Tad M. Heppner, Karthik Raman
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Patent number: 9501640Abstract: In accordance with one embodiment of the present disclosure, a method for determining the similarity between a first data set and a second data set is provided. The method includes performing an entropy analysis on the first and second data sets to produce a first entropy result, wherein the first data set comprises data representative of a first one or more computer files of known content and the second data set comprises data representative of a one or more computer files of unknown content; analyzing the first entropy result; and if the first entropy result is within a predetermined threshold, identifying the second data set as substantially related to the first data set.Type: GrantFiled: September 14, 2011Date of Patent: November 22, 2016Assignee: McAfee, Inc.Inventors: David Neill Beveridge, Abhishek Ajay Karnik, Kevin A. Beets, Tad M. Heppner, Karthik Raman
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Publication number: 20130067579Abstract: In accordance with one embodiment of the present disclosure, a method for determining the similarity between a first data set and a second data set is provided. The method includes performing an entropy analysis on the first and second data sets to produce a first entropy result, wherein the first data set comprises data representative of a first one or more computer files of known content and the second data set comprises data representative of a one or more computer files of unknown content; analyzing the first entropy result; and if the first entropy result is within a predetermined threshold, identifying the second data set as substantially related to the first data set.Type: ApplicationFiled: September 14, 2011Publication date: March 14, 2013Inventors: David Neill Beveridge, Abhishek Ajay Karnik, Kevin A. Beets, Tad M. Heppner, Karthik Raman