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:
Jun. 11, 2024

Filed:

Apr. 08, 2021
Applicant:

Hewlett Packard Enterprise Development Lp, Houston, TX (US);

Inventors:

Priyanka Chandrashekar Bhat, Karnataka, IN;

Madhusoodhana Chari Sesha, Karnataka, IN;

Rashmi Vedi, Karnataka, IN;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); G06F 18/214 (2023.01); G06F 18/23 (2023.01); G06F 18/23213 (2023.01); G06F 18/2413 (2023.01); G06N 20/00 (2019.01); H04L 9/40 (2022.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 18/214 (2023.01); G06F 18/23 (2023.01); G06F 18/23213 (2023.01); G06F 18/24137 (2023.01); H04L 63/0236 (2013.01); H04L 63/1416 (2013.01); H04L 63/1425 (2013.01); H04L 63/20 (2013.01);
Abstract

Examples include detection of unclassified traffic in a network. Some examples use an unsupervised machine learning mechanism for generating a first set of clusters of a first set of samples associated with a first set of time intervals, based at least in part on network traffic over a network, in a first predetermined period of time. Each sample associated with the respective time interval includes distribution of packets based on their packet lengths. In response to retrieving a second set of samples associated with a second set of time intervals, based at least in part on network traffic, a second set of clusters of the second set of samples is generated. It is determined whether one or more features of the second set of clusters vary as compared to one or more features of the first set of clusters of the first set of samples to detect unclassified traffic in the second set of samples.


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