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. 02, 2025

Filed:

Sep. 13, 2023
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

M Krishnakant Achary, Malkangiri, IN;

Priti P Patil, Pune, IN;

Ritesh Kumar, Pune, IN;

Rashmiranjan Pradhan, Irving, TX (US);

Srinivas Babu Tummalapenta, Broomfield, CO (US);

Sridhar Muppidi, Austin, TX (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 21/55 (2013.01); G06N 3/0455 (2023.01);
U.S. Cl.
CPC ...
G06F 21/552 (2013.01); G06F 2221/034 (2013.01); G06N 3/0455 (2023.01);
Abstract

According to one embodiment, a method, computer system, and computer program product for anomaly detection is provided. The embodiment may include receiving login event data of a customer. The embodiment may include labeling each login request of the event data as non-anomalous or anomalous. The embodiment may include performing aggregate feature extraction for each login request. The embodiment may include filtering data of anomalous login requests from data of non-anomalous login requests. The embodiment may include training an autoencoder machine learning model using the data of non-anomalous login requests to learn non-anomalous login request behavior. The embodiment may include passing the data of anomalous login requests through the trained autoencoder ML model to obtain enriched data. The embodiment may include training a classifier model using the enriched data to identify anomalous login requests and output a classification with confidence value.


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