The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 20, 2021

Filed:

Jul. 09, 2019
Applicant:

Mcafee, Llc, San Jose, CA (US);

Inventors:

Adam Wosotowsky, Lilburn, GA (US);

Yonghong Huang, Hillsboro, OR (US);

Eric Peterson, Elizabeth, CO (US);

John Wagener, West Lakeland, MN (US);

Joanna Negrete, Santa Clara, CA (US);

Armando Rodriguez, Parker, CO (US);

Celeste Fralick, Lubbock, TX (US);

Sandeep Chandana, Santa Clara, CA (US);

Assignee:

McAfee, LLC, San Jose, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
H04L 63/1416 (2013.01); G06N 20/00 (2019.01); H04L 63/0236 (2013.01); H04L 63/1425 (2013.01); H04L 63/1466 (2013.01);
Abstract

Methods, apparatus, systems and articles of manufacture for producing generic Internet Protocol (IP) reputation through cross-protocol analysis are disclosed. An example apparatus includes a data collector to gather a first data set representing IP telemetry data for a first protocol, the data collector to gather a second data set representing IP telemetry data for a second protocol different from the first protocol. A label generator is to generate a training data set based on records in the first data set and the second data set having matching IP addresses, the training data set to include combined label indicating whether each of the respective matching IP addresses is malicious. A model trainer is to train a machine learning model using the training data set. A model executor is to, responsive to a request from a client device, execute the machine learning model to determine whether a requested IP address is malicious.


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