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:
Oct. 03, 2023

Filed:

Jan. 18, 2018
Applicant:

Logrhythm Inc., Boulder, CO (US);

Inventors:

Phillip Villella, Boulder, CO (US);

Daniel Kaslovsky, Boulder, CO (US);

Dean Wyatte, Boulder, CO (US);

Assignee:

LogRhythm Inc., Broomfield, CO (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 9/40 (2022.01); H04L 41/14 (2022.01); H04L 43/04 (2022.01); H04L 41/0604 (2022.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G06F 15/76 (2006.01); G06N 3/088 (2023.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/047 (2023.01); G06N 7/01 (2023.01);
U.S. Cl.
CPC ...
H04L 63/1425 (2013.01); G06F 15/76 (2013.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/047 (2023.01); G06N 3/088 (2013.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); H04L 41/0604 (2013.01); H04L 41/14 (2013.01); H04L 43/04 (2013.01); H04L 63/20 (2013.01); H04L 63/1416 (2013.01);
Abstract

A processing pipeline for supporting machine-learning processes for network monitoring and information management as well as specific analytics for particular use cases. The processing pipelinetakes in system data () and pre-processes () the system data. The system data () may include any of the types of data described above including text log files, and categorical data from various sources. The illustrated processing pipelineincludes two branches; a data fitting branch () where a model is developed for the data and a data transformation branch () where the developed model is leveraged to transform live data. For certain event detection use cases, the output of the data transformation branch () includes a score () (e.g., a threat level score) and an attribution ().


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