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. 30, 2026

Filed:

Dec. 18, 2023
Applicant:

Noname Gate Ltd., Tel Aviv-Jaffa, IL;

Inventors:

Idan Tager, Givatayim, IL;

Adi Chen Arbib, Netanya, IL;

Yuval Alkalai Tavori, Ramat Gan, IL;

Shai Meir, Tzur Yitzhak, IL;

Amos Itamar Avni, Tel Aviv, IL;

Assignee:

Akamai Technologies, Inc., Cambridge, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 9/40 (2022.01); H04L 41/142 (2022.01); H04L 41/147 (2022.01); H04L 41/149 (2022.01); H04L 41/16 (2022.01);
U.S. Cl.
CPC ...
H04L 63/14 (2013.01); H04L 41/142 (2013.01); H04L 41/147 (2013.01); H04L 41/149 (2022.05); H04L 41/16 (2013.01); H04L 63/1408 (2013.01);
Abstract

A system and method for mitigating cyber threats based on excessive computing interface usage behaviors. A method includes creating a baseline with respect to at least one computing interface usage metric, wherein each computing interface usage metric is defined with respect to computing interface usage by a user, wherein creating the baseline further comprises training an anomaly detection machine learning model using a training set including a plurality of training values for the at least one computing interface metric; detecting an anomaly in calls made by the user based on at least one deviation from the baseline above a threshold, wherein detecting the anomaly further comprises applying the anomaly detection machine learning model to a plurality of features including values of the at least one computing interface usage metric for the calls made by the user; and mitigating the detected anomaly.


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