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:
Mar. 28, 2023

Filed:

Apr. 30, 2020
Applicant:

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

Inventors:

German Lancioni, San Jose, CA (US);

Jonathan B. King, Hillsboro, OR (US);

Steven Grobman, Flower Mound, TX (US);

Assignee:

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

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); H04L 9/40 (2022.01); G06F 16/245 (2019.01); G06F 16/28 (2019.01); G06F 16/22 (2019.01);
U.S. Cl.
CPC ...
H04L 63/1425 (2013.01); G06F 16/2255 (2019.01); G06F 16/245 (2019.01); G06F 16/285 (2019.01); H04L 63/1416 (2013.01);
Abstract

A method including receiving a feature vector of an unknown sample, computing a MinHash of the unknown sample based on Jaccard-compatible features, querying a Locality Sensitive Hashing forest of known samples with the MinHash of the unknown sample to identify a first subset of known samples that are similar to the unknown sample, receiving for each individual known sample in the first subset, a feature vector including non-Jaccard distance-compatible features, computing a first sub-distance and a second sub-distance between the unknown sample and the known samples in the first subset, calculating a total distance for each known sample in the first subset by combining the first and the second sub-distances, identifying, based on the calculated total distances, a second subset of known samples that are most similar to the unknown sample, and classifying the unknown sample based on the second subset.


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