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:
Dec. 27, 2022

Filed:

Dec. 20, 2019
Applicant:

Rapid7, Inc., Boston, MA (US);

Inventor:

Ralph McTeggart, Belfast, GB;

Assignee:

Rapid7, Inc., Boston, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); H04L 9/40 (2022.01); G06K 9/62 (2022.01); G06N 20/00 (2019.01); H04L 101/622 (2022.01);
U.S. Cl.
CPC ...
H04L 63/1433 (2013.01); G06K 9/6267 (2013.01); G06N 20/00 (2019.01); H04L 2101/622 (2022.05);
Abstract

Disclosed herein are methods, systems, processes, and machine learning models for identifying ephemeral or short lived computing assets in a network. Data indicative of potential ephemeralness associated with the computing assets in the network is received. The received data is processed and provided as input to a logistic machine learning model trainer for classification based on logistic regression. The logistic machine learning model trainer classifies each computing asset as ephemeral or non-ephemeral based on one or more ephemeralness feature characteristics of each of the computing assets that are part of input data. The logistic machine learning model trainer generates a trained logistic machine learning model for identifying new ephemeral computing assets in the network and excluding these new ephemeral computing assets from security operations. The logistic machine learning model is then stored for automatically determining whether a new computing asset in the network is ephemeral.


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