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:
Sep. 09, 2025

Filed:

Oct. 26, 2022
Applicant:

AO Kaspersky Lab, Moscow, RU;

Inventors:

Andrey B. Lavrentyev, Moscow, RU;

Artem M. Vorontsov, Moscow, RU;

Dmitry A. Ivanov, Moscow, RU;

Vyacheslav I. Shkulev, Moscow, RU;

Nikolay N. Demidov, Moscow, RU;

Artyom M. Nechiporuk, Moscow, RU;

Maxim A. Mamaev, Moscow, RU;

Alexander V. Travov, Moscow, RU;

Assignee:

AO Kaspersky Lab, Moscow, RU;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G05B 23/02 (2006.01);
U.S. Cl.
CPC ...
G05B 23/0243 (2013.01); G05B 23/0216 (2013.01); G05B 23/0221 (2013.01); G05B 23/024 (2013.01); G05B 23/0281 (2013.01);
Abstract

A method for diagnostics and monitoring of anomalies in a cyber-physical system (CPS) includes obtaining information related to anomalies identified in the CPS. The obtained information includes at least one value of one or more CPS variables. One or more classifying features of the identified anomalies in the CPS are generated based on the obtained information. Classification of the identified anomalies in the CPS into two or more anomaly classes is performed based on the generated classifying features. Each of the two or more anomaly classes is associated with one or more anomaly characteristics. Diagnostics of anomalies are performed in each of the two or more anomaly classes by calculating values of the anomaly characteristics associated with each of the two or more anomaly classes. Anomalies of each of the two or more anomaly classes are monitored based on the calculated values of the anomaly characteristics associated with each of the two or more anomaly classes.


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